RIVA Multilingual CS Unified Conformer ASR Japanese-English

Speech Recognition: Conformer

Model Overview

Conformer-CTC (around 120M parameters) is trained on ASRSet with over 4280 hours of Japanese(ja-JP)-English(en-JP) code switch speech. The model transcribes speech in Japanese and English alphabet(lower and upper case) along with spaces and punctuations.

Model Architecture

Conformer-CTC [1] model is a non-autoregressive variant of Conformer model [1] for Automatic Speech Recognition which uses CTC loss/decoding instead of Transducer. You may find more info on the detail of this model here: Conformer-CTC Model.

Training

The model was trained on various proprietary and open-source datasets. These datasets include variety of accents, domain specific data for various domains, spontaneous speech and dialogue, all of which contribute to the model’s accuracy. This model delivers WER that is better than or comparable to popular alternate Speech to Text solutions for a range of domains and use cases.

How to Use this Model

The Riva Quick Start Guide is recommended as the starting point for trying out Riva models. For more information on using this model with Riva Speech Services, see the Riva User Guide.

Input

Audio sample that is to be transcribed

Output

This model provides transcribed speech as a string for a given audio sample.

References

[1] Conformer: Convolution-augmented Transformer for Speech Recognition

Licence

By downloading and using the models and resources packaged with Riva Conversational AI, you would be accepting the terms of the Riva license