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Diamondfan / SPAPL_KidsASR

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Benchmarking Children's ASR with Supervised and Self-supervised Speech Foundation Models

Overview

This github repository contains models, scripts and data splits from our paper accepted at Interspeech 2024, which can be found here

Folder Structure

Source code for training different Supervised and Self Supervised models can be found under /src

/egs contains bash scripts to train models on the MyST and CSLU OGI Kids' datasets, as well as scripts to filter these datasets and obtain train test splits

Getting Started

  1. Install Dependencies: transformers==4.32.1 torch evaluate datasets
  2. On older versions of transformers it might be necessary to make minor edits to trainer.py to allow hotloading of Iterable datasets (if streaming is set to True). Follow the instructions in /egs/MyST/README.txt to make the necessary edits.
  3. For training Nemo based models, it is necessary to clone the github repo
  4. To train/evaluate a model a particular dataset, edit the corresponding yaml file stored in the /egs/dataset/config directory, and edit the necessary bash script.

Trained Models

MyST Models - Fully Finetuned

Model MyST test WER Huggingface Link
Whisper tiny 11.6 model
Whisper base 10.4 model
Whisper small 9.3 model
Whisper Medium 8.9 model
Whisper Large 13.0 model
Whisper Large v3 9.1 model
Canary 9.2 model
Parakeet 8.5 model
Wav2vec2.0 Large 11.1 model
HuBERT Large 11.3 model
WavLM Large 10.4 model

OGI Models - Fully Finetuned

Model OGI test WER Huggingface Link
Whisper tiny 3.0 model
Whisper base 2.3 model
Whisper small 1.8 model
Whisper Medium 1.5 model
Whisper Large 1.7 model
Whisper Large v3 1.4 model
Canary 1.5 model
Parakeet 1.8 model
Wav2vec2.0 Large 2.5 model
HuBERT Large 2.5 model
WavLM Large 1.8 model

MyST Models - Whisper small with Data Augmentations

Data Augmentation Myst test WER Huggingface Link
PP 8.8 model
VTLP 9.0 model
SP 8.9 model
SA 9.0 model

MyST Models - Whisper small with PEFT

PEFT Method MyST test WER Huggingface Link
Enc 9.2 model
Dec 9.5 model
LoRA 9.6 model
Prompt 10.4 model
Prefix 10.2 model
Adapter 9.3 model

Citation

If you use this code in your research, please cite it as follows:

@inproceedings{fan24b_interspeech,
  title     = {Benchmarking Children's ASR with Supervised and Self-supervised Speech Foundation Models},
  author    = {Ruchao Fan and Natarajan {Balaji Shankar} and Abeer Alwan},
  year      = {2024},
  booktitle = {Interspeech 2024},
  pages     = {5173--5177},
  doi       = {10.21437/Interspeech.2024-1353},
}