← Search

Mirko Hannemann

2 accepted papers

2024

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

ICASSP 2024accepted

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. In this work, we describe our personalization solution for an end-to-end speech recogn…

Cited by 0SourceScholar
2017

Bayesian joint-sequence models for grapheme-to-phoneme conversion

ICASSP 2017accepted

We describe a fully Bayesian approach to grapheme-to-phoneme conversion based on the joint-sequence model (JSM). Usually, standard smoothed n-gram language models (LM, e.g. Kneser-Ney) are used with JSMs to model graphone sequences (joint grapheme-phoneme pairs). However, we take a Bayesian approach…

Cited by 0SourceScholar