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README.md

@@ -1,60 +1,129 @@
----
-dataset_info:
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: id
-    dtype: string
-  - name: transcript
-    dtype: string
-  - name: language
-    dtype: string
-  - name: emotion
-    dtype: string
-  - name: duration
-    dtype: float32
-  - name: confidence
-    dtype: float32
-  - name: source_url
-    dtype: string
-  - name: human_reviewed
-    dtype: bool
-  - name: snr_db
-    dtype: float32
-  - name: speech_ratio
-    dtype: float32
-  - name: quality_score
-    dtype: float32
-  - name: speaker_id
-    dtype: string
-  - name: genre
-    dtype: string
-  - name: accent
-    dtype: string
-  - name: video_id
-    dtype: string
-  - name: segment_index
-    dtype: int32
-  - name: start_time
-    dtype: float32
-  - name: end_time
-    dtype: float32
-  splits:
-  - name: en
-    num_bytes: 110486845.0
-    num_examples: 127
-  - name: hi
-    num_bytes: 41000921.0
-    num_examples: 48
-  download_size: 142535015
-  dataset_size: 151487766.0
-configs:
-- config_name: default
-  data_files:
-  - split: en
-    path: data/en-*
-  - split: hi
-    path: data/hi-*
----
+---
+license: cc-by-4.0
+language:
+  - en
+  - hi
+tags:
+  - tts
+  - text-to-speech
+  - indian-english
+  - hindi
+  - speech
+  - single-speaker
+  - sarvam
+  - audio
+task_categories:
+  - text-to-speech
+pretty_name: Sarvam Indian TTS Dataset (en-IN + hi-IN)
+size_categories:
+  - 1K<n<10K
+---
+
+# Sarvam Indian TTS Dataset
+
+A curated Text-to-Speech dataset containing **Indian English** and **Hindi** 
+single-speaker audio segments, built as part of the Sarvam AI hiring assignment.
+
+## Dataset Summary
+
+| Property | Value |
+|---|---|
+| Total duration | 78.8 minutes |
+| English (en-IN) | 57.5 minutes |
+| Hindi (hi-IN) | 21.3 minutes |
+| Total segments | 175 |
+| Human reviewed | 99.4% |
+| Mean quality score | 92.1/100 |
+| Mean SNR | 49.0 dB |
+| Mean ASR confidence | 0.900 |
+
+## Dataset Card
+
+### Data Collection
+
+Audio sourced from YouTube educational and motivational content featuring 
+single speakers with minimal background noise. All audio was processed through:
+
+1. **Speaker Diarization** (Sarvam API) — isolate dominant speaker
+2. **Segmentation** — 15–60 second clips, no overlap
+3. **Quality Filtering** — SNR ≥ 15 dB, speech ratio ≥ 65%
+4. **ASR Transcription** (Sarvam saarika:v2) — with word timestamps
+5. **Emotion Tagging** (Sarvam LLM) — style/prosody labels
+6. **Human Review** — transcript correction and quality verification
+
+### Audio Format
+
+- Format: WAV (PCM 16-bit)
+- Sample rate: 16,000 Hz
+- Channels: Mono
+
+### Schema
+
+```
+id              — unique segment identifier
+audio           — WAV audio file (HF Audio feature)
+transcript      — verbatim speech transcript
+language        — en (Indian English) | hi (Hindi)
+emotion         — style label (see taxonomy below)
+duration        — segment length in seconds
+confidence      — ASR confidence score [0, 1]
+source_url      — original YouTube URL
+human_reviewed  — whether a human verified this segment
+```
+
+### Emotion Taxonomy
+
+  - informative: 158
+  - emphatic: 16
+  - energetic: 1
+
+### Source Videos
+
+| Language | Description | Accent |
+|---|---|---|
+| English | Stanford GSB lecture (Matt Abrahams) | American English |
+| English | Indian tech talk | Indian English |
+| Hindi | Hindi motivational speech | Standard Hindi |
+| Hindi | Hindi motivational speech | Standard Hindi |
+
+> **Note on English accent**: The primary English source (Stanford lecture) 
+> features an American English speaker. This is documented transparently in 
+> the `accent` metadata field. The Sarvam en-IN ASR model was used for 
+> transcription regardless.
+
+### Pipeline
+
+Full reproducible pipeline available at: https://github.com/[username]/sarvam-tts-dataset
+
+```
+scripts/
+  00_setup_env.py         # environment validation
+  01_download_audio.py    # yt-dlp download
+  02_convert_audio.py     # ffmpeg → 16kHz mono WAV
+  03_diarization.py       # Sarvam speaker diarization
+  04_segment_audio.py     # 15–60s segmentation
+  05_asr_transcription.py # Sarvam saarika:v2 ASR
+  06_emotion_tagging.py   # Sarvam LLM emotion labels
+  07_quality_scoring.py   # composite quality score
+  08_human_review.py      # interactive CLI review
+  09_build_metadata.py    # final CSV/JSONL assembly
+  10_dataset_statistics.py # stats + visualisations
+  11_upload_huggingface.py # HF Hub upload
+```
+
+### Licensing
+
+- Dataset: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- Source videos used under YouTube's fair use provisions for research/education
+- Transcripts are derived works; see individual source URLs for original content
+
+### Citation
+
+```bibtex
+@dataset{sarvam_tts_dataset_2025,
+  title={Sarvam Indian TTS Dataset},
+  year={2025},
+  url={https://huggingface.co/Avishii0309/sarvam-tts-dataset},
+  note={Indian English and Hindi single-speaker TTS dataset}
+}
+```