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README.md

@@ -1,118 +1,67 @@
----
-dataset_info:
-- config_name: indian_english
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 24000
-  - name: text
-    dtype: string
-  - name: normalized_text
-    dtype: string
-  - name: language
-    dtype: string
-  - name: language_code
-    dtype: string
-  - name: emotion
-    dtype: string
-  - name: style
-    dtype: string
-  - name: emotion_confidence
-    dtype: float32
-  - name: tag_source
-    dtype: string
-  - name: speaker_id
-    dtype: string
-  - name: duration
-    dtype: float32
-  - name: snr_db
-    dtype: float32
-  - name: source_video_id
-    dtype: string
-  - name: source_url
-    dtype: string
-  - name: source_channel
-    dtype: string
-  - name: license
-    dtype: string
-  - name: segment_start
-    dtype: float32
-  - name: segment_end
-    dtype: float32
-  - name: sample_rate
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 82085131.0
-    num_examples: 134
-  - name: validation
-    num_bytes: 4559768.0
-    num_examples: 8
-  download_size: 85990215
-  dataset_size: 86644899.0
-- config_name: telugu
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 24000
-  - name: text
-    dtype: string
-  - name: normalized_text
-    dtype: string
-  - name: language
-    dtype: string
-  - name: language_code
-    dtype: string
-  - name: emotion
-    dtype: string
-  - name: style
-    dtype: string
-  - name: emotion_confidence
-    dtype: float32
-  - name: tag_source
-    dtype: string
-  - name: speaker_id
-    dtype: string
-  - name: duration
-    dtype: float32
-  - name: snr_db
-    dtype: float32
-  - name: source_video_id
-    dtype: string
-  - name: source_url
-    dtype: string
-  - name: source_channel
-    dtype: string
-  - name: license
-    dtype: string
-  - name: segment_start
-    dtype: float32
-  - name: segment_end
-    dtype: float32
-  - name: sample_rate
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 82651985.0
-    num_examples: 133
-  - name: validation
-    num_bytes: 4636028.0
-    num_examples: 7
-  download_size: 87020068
-  dataset_size: 87288013.0
-configs:
-- config_name: indian_english
-  data_files:
-  - split: train
-    path: indian_english/train-*
-  - split: validation
-    path: indian_english/validation-*
-- config_name: telugu
-  data_files:
-  - split: train
-    path: telugu/train-*
-  - split: validation
-    path: telugu/validation-*
----
+---
+license: cc-by-4.0
+task_categories:
+- text-to-speech
+language:
+- en
+- te
+tags:
+- tts
+- speech
+- indian-languages
+- telugu
+- indian-english
+- emotion
+- single-speaker
+pretty_name: Indian English + Telugu Single-Speaker TTS (emotion-tagged)
+size_categories:
+- n<1K
+configs:
+- config_name: indian_english
+  data_files: indian_english/**
+- config_name: telugu
+  data_files: telugu/**
+---
+
+# Indian English + Telugu Single-Speaker TTS Dataset (emotion-tagged)
+
+Clean, single-speaker audio clips sourced from YouTube, transcribed with **Sarvam**
+ASR, segmented with diarization, and labeled with emotion/style tags. Built as a
+data-quality / curation exercise.
+
+## Contents
+- **Indian English** (`indian_english`): 30.05 min, 142 clips, 5 speakers; emotions: {'neutral': 31, 'calm': 31, 'sad': 30, 'excited': 30, 'angry': 12, 'fearful': 5, 'happy': 3}
+- **Telugu** (`telugu`): 30.25 min, 140 clips, 6 speakers; emotions: {'calm': 25, 'neutral': 24, 'angry': 24, 'excited': 24, 'sad': 24, 'fearful': 9, 'happy': 7, 'surprised': 3}
+
+Total: **60.3 minutes**.
+
+## Schema
+`audio` (24 kHz mono), `text`, `normalized_text`, `language`, `language_code`,
+`emotion` (neutral, happy, sad, angry, excited, calm, fearful, surprised), `style` (narrative, conversational, formal, expressive, whisper), `emotion_confidence`, `tag_source`
+(`auto`/`human`), `speaker_id`, `duration`, `snr_db`, `source_video_id`,
+`source_url`, `source_channel`, `license`, `segment_start`, `segment_end`,
+`sample_rate`.
+
+## How it was built
+1. Curated single-speaker YouTube sources (audiobooks, lectures, news, storytelling).
+2. **Sarvam batch STT** (`saaras:v3`) with diarization + timestamps for structure.
+3. Silence-snapped segmentation into 3–25 s clips (single speaker only).
+4. **Sarvam realtime STT** (`saarika:v2.5`) per clip for clip-accurate transcripts.
+5. Automated quality gates (clipping, SNR, silence, music/noise bed, ASR confidence, dedup).
+6. Hybrid emotion tagging: per-speaker-normalized acoustic features + Sarvam LLM,
+   with an acoustic whisper override.
+7. Human review (listen, fix transcripts, relabel) — **human labels override automated ones**.
+8. Light loudness normalization (dynamics preserved), balanced emotion selection.
+
+## Audio
+24 kHz mono WAV. Loudness lightly normalized (~-20 LUFS, peak −1 dBFS) WITHOUT
+limiting, so the prosodic dynamics that carry emotion are preserved.
+
+## Ethics & licensing
+Sourced from YouTube for research; clips are short and transformative. Per-clip
+provenance (`source_url`, `source_channel`, `license`) is retained. Respect the
+original creators' rights; remove clips on request.
+
+## Limitations
+Emotion tags are heuristic (acoustic + LLM, partly human-verified) and may be
+imperfect for subtle prosody. See the project report for iteration notes.