Datasets:
metadata
language:
- en
license: cc-by-4.0
task_categories:
- text-to-speech
tags:
- dac
- audio-tokens
- speech
- tts
- codebook
- descript-audio-codec
- librispeech
- 16khz
pretty_name: Speech DAC Tokens 16kHz (2 Codebooks)
size_categories:
- 10K<n<100K
Speech DAC Tokens 16kHz (2 Codebooks)
Pre-tokenized speech dataset using DAC at 16kHz with 2 codebooks. Optimized for speech TTS training — 16kHz captures the full speech frequency range without wasting capacity on inaudible frequencies.
Why 16kHz?
- Speech lives below 8kHz — 16kHz sample rate is sufficient (Nyquist)
- 50 tokens/sec per codebook vs 87 at 44kHz — shorter sequences, faster training
- 2 codebooks at 16kHz produce intelligible speech — verified by listening tests
- No resampling needed — LibriSpeech is natively 16kHz
Dataset Summary
| Stat | Value |
|---|---|
| Total samples | 132,479 |
| Total audio | ~464 hours |
| Source | LibriSpeech clean-100 + clean-360 |
| Language | English |
| DAC model | 16kHz, 2 of 12 codebooks |
| Codebook size | 1,024 entries each |
| Tokens per second | 100 (50/codebook x 2) |
| Token sequence length | 149-2,047 (mean: 1,327) |
Format
| Column | Type | Description |
|---|---|---|
text |
string | Original text transcription |
prompt |
string | {text}<|audio_start|><|c1_X|><|c2_Y|>...<|audio_end|> |
input_ids |
list[int] | Pre-tokenized with Qwen3-0.6B + 2cb DAC tokens |
attention_mask |
list[int] | All 1s |
labels |
list[int] | Copy of input_ids |
n_audio_frames |
int | Number of DAC time frames |
n_tokens |
int | Total token count |
Audio tokens interleaved: c1, c2, c1, c2, ... per frame.
Related
- Training code: treadon/ri-tts on GitHub
- 44kHz dataset (3cb): treadon/speech-dac-tokens-3cb (241K samples, kept for reference)
Citation
@inproceedings{panayotov2015librispeech,
title={Librispeech: an ASR corpus based on public domain audio books},
author={Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev},
booktitle={ICASSP},
year={2015}
}