Librispeech: An ASR corpus based on public domain audio books
Vassil Panayotov low, Guoguo Chen low, Daniel Povey, Sanjeev Khudanpur
This paper introduces a new corpus of read English speech, suitable for training and evaluating speech recognition systems. The LibriSpeech corpus is derived from audiobooks that are part of the LibriVox project, and contains 1000 hours of speech sampled at 16 kHz. We have made the corpus freely available for download, along with separately prepared language-model training data and pre-built language models. We show that acoustic models trained on LibriSpeech give lower error rate on the Wall Street Journal (WSJ) test sets than models trained on WSJ itself. We are also releasing Kaldi scripts that make it easy to build these systems.
Citation edge evidence
- SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition→Librispeech: An ASR corpus based on public domain audio booksLegacy edge — source detail unavailable
- Conformer: Convolution-augmented Transformer for Speech Recognition→Librispeech: An ASR corpus based on public domain audio booksLegacy edge — source detail unavailable
- In-Kernel Aggregation and Broadcast Acceleration for Distributed Communication→Librispeech: An ASR corpus based on public domain audio booksLegacy edge — source detail unavailable
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Librispeech: An ASR corpus based on public domain audio booksLegacy edge — source detail unavailable
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing→Librispeech: An ASR corpus based on public domain audio booksLegacy edge — source detail unavailable
- Librispeech: An ASR corpus based on public domain audio books→Identification of common molecular subsequencesLegacy edge — source detail unavailable
- Librispeech: An ASR corpus based on public domain audio books→Kaldi Speech Recognition ToolkitLegacy edge — source detail unavailable
- Librispeech: An ASR corpus based on public domain audio books→SRILM - an extensible language modeling toolkitLegacy edge — source detail unavailable
- Librispeech: An ASR corpus based on public domain audio books→Improved backing-off for M-gram language modelingLegacy edge — source detail unavailable
- SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition→Kaldi Speech Recognition ToolkitLegacy edge — source detail unavailable
- In-Kernel Aggregation and Broadcast Acceleration for Distributed Communication→SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionLegacy edge — source detail unavailable
- Conformer: Convolution-augmented Transformer for Speech Recognition→SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionLegacy edge — source detail unavailable
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing→SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionLegacy edge — source detail unavailable
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing→In-Kernel Aggregation and Broadcast Acceleration for Distributed CommunicationLegacy edge — source detail unavailable
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing→Conformer: Convolution-augmented Transformer for Speech RecognitionLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Identification of common molecular subsequences | 1981 | 10,144 |
| Kaldi Speech Recognition Toolkit | 2024 | 4,895 |
| SRILM - an extensible language modeling toolkit | 2002 | 4,404 |
| Improved backing-off for M-gram language modeling | 2002 | 1,500 |
What cites it, inside the corpus
Links
Topics
| Speech Recognition and Synthesis | Computer Science |
| Music and Audio Processing | Computer Science |
| Speech and Audio Processing | Computer Science |
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Nothing in this record contradicts itself and no field we check is missing.
- supports4 author record(s) attached.
- supports29 reference(s) recorded.
- supportsThe DOI's year agrees with the publication year.
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Provenance
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