Datasets:

padmanabansambath
/

vui-english-nonverbaltts-fluac-q9-22khz-v1

id large_string	dataset large_string	split large_string	source_path large_string	speaker large_string	duration_sec float64	sample_rate int64	num_codebooks int64	num_frames int64	text_raw large_string	text_clean large_string	text_no_inline large_string	text_vui large_string	text_no_inline_vui large_string	text_g large_string	text_g_vui large_string	text_inline large_string	text_inline_vui large_string	text_g_inline large_string	text_g_inline_vui large_string	text_train_default large_string	text_train_nograph large_string	conditioned_text large_string	text large_string	grapheme_units list	grapheme_word_structure list	prosody_tags_original list	prosody_tags_vui list	prosody_tags_removed list	prosody_classes list	prompt_tags_original list	prompt_prosody_classes list	has_inline_vui bool	has_pause bool	has_laugh bool	has_breath bool	has_emphasis bool	has_speed bool	fluac_codes list	gender large_string	emotion large_string	duration_sec_original float64	code_min int64	code_max int64	has_mixed_script bool	language large_string	verification_passed null	audio_quality null	pipeline_version large_string	conditioned_text_bytes int64	text_clean_bytes int64	text_g_vui_bytes int64	text_g_inline_vui_bytes int64
ex04-ex02_calm_006-ex04_calm_css003	deepvk_NonverbalTTS	valid	ex04-ex02_calm_006-ex04_calm_css003.wav	ex04	14.968	22,050	9	323	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, 🌬️ if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this.	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	I mean, yeah, it makes me a little bit scared, but it also makes me a little bit relaxed in the way that, like, [breath] if the ocean is so vast and we're part of all of that, we are a part of this. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 169, 923, 484, 538, 346, 499, 539, 204, 589, 337, 249, 258, 570, 426, 281, 97, 248, 296, 144, 376, 72, 144, 176, 188, 539, 235, 251, 564, 525, 283, 740, 489, 297, 501, 298, ...	f	other	14.968	0	998	false	en	null	null	english_nonverbaltts_v3	206	198	197	206
id03621/JjkkzsW0054/00063	deepvk_NonverbalTTS	train	id03621_JjkkzsW0054_00063.wav	id03621	12.544	22,050	9	271	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. 🌬️	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look.	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look.	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	The entire movie when I was watching it, I was kind of chuckling a little bit because for me, I was like, oh, I remember that. It was really funny. We were having some jokes afterwards and went out to eat sandwiches after that. Like little things that made me look. [breath] [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 722, 176, 371, 371, 569, 171, 570, 725, 773, 780, 769, 289, 776, 361, 178, 539, 777, 536, 761, 763, 765, 770, 369, 569, 345, 761, 724, 761, 171, 139, 569, 547, 572, 571, 764,...	f	happy	12.544	3	998	false	en	null	null	english_nonverbaltts_v3	282	274	273	282
id10068/mSqgYQVmXps/00002	deepvk_NonverbalTTS	train	id10068_mSqgYQVmXps_00002.wav	id10068	12.2881	22,050	9	265	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so 🌬️ I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked.	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	I neededed to. I didn't really know, I guess, how to or I didn't really know what to say, but anyways, I know I'm going to Chicago and I'm having a talk at UIC, so [breath] I know that a lot of questions will be asked. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 178, 772, 377, 330, 587, 380, 781, 570, 132, 323, 574, 574, 771, 562, 761, 561, 339, 982, 652, 940, 980, 972, 851, 771, 780, 771, 570, 578, 554, 370, 338, 369, 369, 128, 572,...	f	neutral	12.2881	4	999	false	en	null	null	english_nonverbaltts_v3	226	218	217	226
ex03-ex01_calm_001-ex01_calm_css036	deepvk_NonverbalTTS	train	ex03-ex01_calm_001-ex01_calm_css036.wav	ex01	7.552	22,050	9	163	watch the sunrise with me and we'd breathe in the 🌬️ ocean air and	watch the sunrise with me and we'd breathe in the [breath] ocean air and.	watch the sunrise with me and we'd breathe in the ocean air and.	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the ocean air and. [pause]	watch the sunrise with me and we'd breathe in the ocean air and.	watch the sunrise with me and we'd breathe in the ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and.	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and.	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	watch the sunrise with me and we'd breathe in the [breath] ocean air and. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 152, 64, 240, 257, 545, 658, 657, 699, 754, 410, 458, 544, 352, 656, 937, 892, 738, 60, 53, 85, 51, 746, 458, 45, 93, 44, 507, 650, 699, 506, 274, 714, 915, 747, 451, 490...	m	sad	7.552	3	998	false	en	null	null	english_nonverbaltts_v3	81	73	72	81
ex04-ex01_laughing_001-ex01_laughing_css027	deepvk_NonverbalTTS	train	ex04-ex01_laughing_001-ex01_laughing_css027.wav	ex01	2.9974	22,050	9	65	It was a good time. 🌬️ 😤	It was a good time. [breath] [sigh]	It was a good time.	It was a good time. [breath] [sigh] [pause]	It was a good time. [pause]	It was a good time.	It was a good time. [pause]	It was a good time. [breath] [sigh]	It was a good time. [breath] [sigh] [pause]	It was a good time. [breath] [sigh]	It was a good time. [breath] [sigh] [pause]	It was a good time. [breath] [sigh] [pause]	It was a good time. [breath] [sigh] [pause]	It was a good time. [breath] [sigh] [pause]	It was a good time. [breath] [sigh] [pause]	[]	[]	[ "[breath]", "[sigh]" ]	[ "[breath]", "[sigh]", "[breath]", "[sigh]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 380, 579, 82, 122, 42, 242, 284, 122, 192, 57, 129, 680, 369, 682, 771, 251, 51, 227, 562, 185, 332, 676, 490, 192, 192, 3, 570, 451, 491, 731, 692, 508, 707, 352, 544, 1...	m	happy	2.9974	3	998	false	en	null	null	english_nonverbaltts_v3	43	35	27	43
id05049/sBIj9k6Fc80/00437	deepvk_NonverbalTTS	train	id05049_sBIj9k6Fc80_00437.wav	id05049	14.976	22,050	9	323	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to 🌬️ their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people.	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	Mark is a father from California, Jenny Beth is a mother from Atlanta. And I went to [breath] their convention just to hang out. I mean, I wasn't speaking, but just to hang out to meet these people and talk to them. And I saw two thousand people. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 546, 706, 778, 578, 307, 587, 337, 171, 377, 162, 345, 745, 737, 939, 379, 539, 388, 131, 985, 530, 364, 164, 977, 929, 747, 697, 507, 785, 380, 164, 737, 937, 346, 546, 346,...	m	neutral	14.976	6	996	false	en	null	null	english_nonverbaltts_v3	254	246	245	254
ex01_sad_00265	deepvk_NonverbalTTS	train	ex01_sad_00265.wav	ex01	3.5414	22,050	9	77	So, Mom, 🌬️ how've you been?	So, Mom, [breath] how've you been?	So, Mom, how've you been?	So, Mom, [breath] how've you been? [pause]	So, Mom, how've you been? [pause]	So, Mom, how've you been?	So, Mom, how've you been? [pause]	So, Mom, [breath] how've you been?	So, Mom, [breath] how've you been? [pause]	So, Mom, [breath] how've you been?	So, Mom, [breath] how've you been? [pause]	So, Mom, [breath] how've you been? [pause]	So, Mom, [breath] how've you been? [pause]	So, Mom, [breath] how've you been? [pause]	So, Mom, [breath] how've you been? [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 192, 192, 178, 51, 53, 266, 931, 698, 641, 448, 720, 457, 265, 105, 136, 177, 152, 385, 657, 649, 690, 682, 625, 289, 353, 136, 384, 152, 392, 376, 312, 368, 368, 144, 168, ...	m	sad	3.5414	0	988	false	en	null	null	english_nonverbaltts_v3	42	34	33	42
ex03-ex01_sleepy_003-ex01_sleepy_css008	deepvk_NonverbalTTS	train	ex03-ex01_sleepy_003-ex01_sleepy_css008.wav	ex01	12.308	22,050	9	266	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, 🌬️ just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit.	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	Yeah, I know. Never mind. I think you're going to have the world's most stinkiest, [breath] just massive, flatulent shit. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 185, 242, 473, 266, 468, 741, 500, 629, 909, 668, 667, 459, 273, 507, 667, 626, 865, 665, 226, 275, 758, 226, 98, 693, 72, 29, 340, 88, 499, 603, 300, 232, 491, 636, 761, ...	m	disgusted	12.308	2	997	false	en	null	null	english_nonverbaltts_v3	129	121	120	129
id10931/DxNk7tLkPbM/00015	deepvk_NonverbalTTS	train	id10931_DxNk7tLkPbM_00015.wav	id10931	4.8001	22,050	9	104	There was an interview on sixty minutes with Mike Williams and he talked about that moment. 🗣️	There was an interview on sixty minutes with Mike Williams and he talked about that moment.	There was an interview on sixty minutes with Mike Williams and he talked about that moment.	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment.	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment.	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment.	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	There was an interview on sixty minutes with Mike Williams and he talked about that moment. [pause]	[]	[]	[]	[]	[ "🗣" ]	[]	[]	[]	false	true	false	false	false	false	[ [ 669, 755, 547, 506, 370, 337, 371, 172, 554, 905, 755, 341, 507, 778, 587, 340, 739, 749, 994, 340, 596, 667, 947, 786, 374, 174, 547, 538, 373, 173, 508, 753, 795, 701, 756,...	m	neutral	4.8001	10	997	false	en	null	null	english_nonverbaltts_v3	99	91	99	99
id07711/S8YWigT3Qu4/00117	deepvk_NonverbalTTS	train	id07711_S8YWigT3Qu4_00117.wav	id07711	8.736	22,050	9	189	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. 🌬️ So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature.	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	Where a bank gives you a loan and then they sell it to five hundred different people and bondholders and so there isn't somebody to talk to across the desk if you go to a bank. [breath] So you have mature. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 184, 530, 778, 771, 690, 731, 778, 729, 377, 344, 536, 937, 747, 739, 746, 577, 337, 177, 377, 176, 377, 689, 185, 547, 724, 581, 386, 306, 178, 537, 169, 368, 177, 369, 132,...	m	neutral	8.736	2	980	false	en	null	null	english_nonverbaltts_v3	213	205	204	213
ex03-ex01_disgusted_006-ex03_disgusted_css015	deepvk_NonverbalTTS	train	ex03-ex01_disgusted_006-ex03_disgusted_css015.wav	ex03	10.0587	22,050	9	217	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... 🌬️ It's like they just... It's like just a massive... 😤	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... It's like they just... It's like just a massive...	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... It's like they just... It's like just a massive... [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... It's like they just... It's like just a massive...	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... It's like they just... It's like just a massive... [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	That one, I can't even tell if it's two socks or one sock. Is that a pair? Oh my god, it's like... [breath] It's like they just... It's like just a massive... [sigh] [pause]	[]	[]	[ "[breath]", "[sigh]" ]	[ "[breath]", "[sigh]", "[breath]", "[sigh]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 107, 330, 523, 282, 50, 340, 296, 16, 65, 34, 542, 973, 604, 440, 689, 682, 691, 894, 283, 192, 42, 491, 332, 242, 339, 301, 9, 509, 562, 337, 304, 53, 252, 694, 481, 528...	m	happy	10.0587	2	997	false	en	null	null	english_nonverbaltts_v3	173	165	157	173
ex01-ex02_whisper_004-ex01_whisper_css012	deepvk_NonverbalTTS	train	ex01-ex02_whisper_004-ex01_whisper_css012.wav	ex01	15	22,050	9	323	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. 🌬️ And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s.	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	Yeah, it soaks into the, not the actual paint, but the overcoat of the paint. It kind of lays the resin. [breath] And so what they do is they remove that resin, they clean the paint. And especially because, you know, we're talking like, this is like the 1400s, 1500s. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 24, 129, 257, 100, 484, 686, 483, 89, 444, 253, 88, 28, 14, 207, 721, 640, 256, 421, 47, 50, 341, 410, 257, 445, 242, 338, 404, 59, 243, 724, 443, 256, 262, 321, 250, 65,...	m	neutral	15	2	997	false	en	null	null	english_nonverbaltts_v3	275	267	266	275
id03272/E6ao8iPr3xY/00069	deepvk_NonverbalTTS	train	id03272_E6ao8iPr3xY_00069.wav	id03272	6.144	22,050	9	133	The greatest human being I could have ever met and ever worked with. 🌬️ And he validated my career.	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career.	The greatest human being I could have ever met and ever worked with. And he validated my career.	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. And he validated my career.	The greatest human being I could have ever met and ever worked with. And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career.	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career.	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	The greatest human being I could have ever met and ever worked with. [breath] And he validated my career. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 330, 779, 532, 581, 571, 572, 762, 140, 322, 323, 372, 379, 730, 787, 571, 569, 569, 331, 539, 579, 580, 364, 372, 579, 337, 523, 578, 570, 685, 779, 569, 163, 580, 538, 780,...	f	other	6.144	6	997	false	en	null	null	english_nonverbaltts_v3	113	105	104	113
ex04-ex02_fearful_001-ex02_fearful_css017	deepvk_NonverbalTTS	train	ex04-ex02_fearful_001-ex02_fearful_css017.wav	ex02	2.7093	22,050	9	59	I don't... 🌬️ Okay.	I don't... [breath] Okay.	I don't... Okay.	I don't... [breath] Okay. [pause]	I don't... Okay. [pause]	I don't... Okay.	I don't... Okay. [pause]	I don't... [breath] Okay.	I don't... [breath] Okay. [pause]	I don't... [breath] Okay.	I don't... [breath] Okay. [pause]	I don't... [breath] Okay. [pause]	I don't... [breath] Okay. [pause]	I don't... [breath] Okay. [pause]	I don't... [breath] Okay. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 192, 560, 726, 532, 93, 692, 689, 368, 884, 285, 484, 328, 171, 484, 243, 322, 322, 490, 522, 376, 363, 445, 484, 244, 402, 328, 192, 370, 283, 282, 330, 323, 521, 520, 392, ...	f	sad	2.7093	1	993	false	en	null	null	english_nonverbaltts_v3	33	25	24	33
id01617/oddqJy14KLo/00307	deepvk_NonverbalTTS	train	id01617_oddqJy14KLo_00307.wav	id01617	28.48	22,050	9	614	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	I hope that I won't be seeing any of them. They'll be behind me. But you know, it's it's it's going to be a great race and that's what's so fantastic about this sport. I think the women the women's field is as deep and as strong as the men's field and it's going to be as exciting, if not more, for for the spectators an...	[]	[]	[ "[laugh]" ]	[ "[laugh]", "[laugh]" ]	[]	[ "laugh_smile" ]	[]	[]	true	true	true	false	false	false	[ [ 777, 923, 734, 563, 571, 973, 572, 787, 176, 168, 168, 377, 539, 787, 685, 577, 569, 971, 724, 776, 778, 771, 176, 378, 579, 122, 170, 731, 588, 581, 569, 779, 765, 529, 378,...	f	happy	28.48	5	999	false	en	null	null	english_nonverbaltts_v3	486	478	478	486
id08125/uBqQ6o2Ca18/00342	deepvk_NonverbalTTS	train	id08125_uBqQ6o2Ca18_00342.wav	id08125	5.76	22,050	9	125	For example, people could understand Holocaust, 🌬️ but small nations don't have that.	For example, people could understand Holocaust, [breath] but small nations don't have that.	For example, people could understand Holocaust, but small nations don't have that.	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, but small nations don't have that. [pause]	For example, people could understand Holocaust, but small nations don't have that.	For example, people could understand Holocaust, but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that.	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that.	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	For example, people could understand Holocaust, [breath] but small nations don't have that. [pause]	[]	[]	[ "[breath]" ]	[ "[breath]", "[breath]" ]	[]	[ "breath_thinking" ]	[]	[]	true	true	false	true	false	false	[ [ 363, 377, 938, 545, 172, 362, 930, 738, 337, 529, 736, 169, 578, 794, 328, 537, 378, 169, 737, 337, 378, 730, 771, 529, 554, 172, 169, 770, 730, 554, 362, 362, 369, 760, 849,...	f	neutral	5.76	1	989	false	en	null	null	english_nonverbaltts_v3	99	91	90	99

End of preview. Expand in Data Studio

VUI English NonverbalTTS FLUAC Q9 22kHz v1

English NonverbalTTS subset prepared for VUI decoder distillation.

Processing

Source dataset: deepvk/NonverbalTTS
Text source: validated Result / fallback text
Audio codec: FLUAC Q9 22kHz
fluac_codes shape: [9, T]
No EOS/PAD frames included
Training collator should add EOS if needed
Final [pause] is appended to match VUI-style prompts
Unsupported emoji/nonverbal events are dropped
Supported mappings:
- 🌬 -> [breath]
- 🤣 -> [laugh]
- 😤, 😖 -> [sigh]
Unsupported dropped examples include cough/sniff/sneeze/snore/grunt-like events.

Stats

Records: 2444
Duration: 6.38 hours
Splits: train 2066, valid 343, test 35
Max frames: 643
Emoji rows: 0
Prosody counts:
- [breath]: 4210
- [sigh]: 1088
- [laugh]: 294

Main columns

text_train_nograph
text_train_default
conditioned_text
text
fluac_codes
duration_sec
num_frames
split
speaker
emotion

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