Personalization of CTC-based End-to-End Speech Recognition Using Pronunciation-Driven Subword Tokenization

no code implementations • 16 Oct 2023 • Zhihong Lei, Ernest Pusateri, Shiyi Han, Leo Liu, MingBin Xu, Tim Ng, Ruchir Travadi, Youyuan Zhang, Mirko Hannemann, Man-Hung Siu, Zhen Huang

Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as contact names remains a challenge.

Automatic Speech Recognition speech-recognition +1

Acoustic Model Fusion for End-to-end Speech Recognition

no code implementations • 10 Oct 2023 • Zhihong Lei, MingBin Xu, Shiyi Han, Leo Liu, Zhen Huang, Tim Ng, Yuanyuan Zhang, Ernest Pusateri, Mirko Hannemann, Yaqiao Deng, Man-Hung Siu

Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Space-Efficient Representation of Entity-centric Query Language Models

no code implementations • 29 Jun 2022 • Christophe Van Gysel, Mirko Hannemann, Ernest Pusateri, Youssef Oualil, Ilya Oparin

Virtual assistants make use of automatic speech recognition (ASR) to help users answer entity-centric queries.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Connecting and Comparing Language Model Interpolation Techniques

no code implementations • 26 Aug 2019 • Ernest Pusateri, Christophe Van Gysel, Rami Botros, Sameer Badaskar, Mirko Hannemann, Youssef Oualil, Ilya Oparin

In this work, we uncover a theoretical connection between two language model interpolation techniques, count merging and Bayesian interpolation.

Language Modelling