Unispeech Large 1500h Cv Timit
This model is an automatic speech recognition model fine-tuned on the TIMIT_ASR dataset based on microsoft/unispeech-large-1500h-cv, achieving a word error rate (WER) of 21.96% on the evaluation set.
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Release Time : 3/2/2022
Model Overview
An automatic speech recognition model optimized for English speech recognition tasks, particularly suitable for speech scenarios similar to the TIMIT dataset.
Model Features
Fine-tuned Based on Large-scale Pre-trained Model
Fine-tuned on the UniSpeech-Large model pre-trained with 1500 hours of speech data, featuring robust speech feature extraction capabilities.
Optimized for TIMIT Dataset
Specifically optimized for the TIMIT ASR dataset, demonstrating excellent performance on this dataset.
Low Word Error Rate
Achieved a word error rate (WER) of 21.96% on the evaluation set.
Model Capabilities
English Speech Recognition
Continuous Speech-to-Text
Phoneme-level Recognition
Use Cases
Speech Recognition Research
TIMIT Dataset Speech Recognition Benchmark
Can be used for benchmark testing and comparison of speech recognition algorithms.
WER 21.96%
Educational Applications
English Pronunciation Assessment
Can be used to evaluate the pronunciation accuracy of English learners.
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