164 citations · 535 across the 44 of their papers we have counts for
7 papers · 1 filter
O-1: Self-training with Oracle and 1-best Hypothesis
Murali Karthick Baskar, Andrew Rosenberg, Bhuvana Ramabhadran +1
We introduce O-1, a new self-training objective to reduce training bias and unify training and evaluation metrics for speech recognition. O-1 is a faster variant of Expected Minimu…
Using Text Injection to Improve Recognition of Personal Identifiers in Speech
Yochai Blau, Rohan Agrawal, Lior Madmony +7
Accurate recognition of specific categories, such as persons' names, dates or other identifiers is critical in many Automatic Speech Recognition (ASR) applications. As these catego…
Large-scale Language Model Rescoring on Long-form Data
Tongzhou Chen, Cyril Allauzen, Yinghui Huang +8
In this work, we study the impact of Large-scale Language Models (LLM) on Automated Speech Recognition (ASR) of YouTube videos, which we use as a source for long-form ASR. We demon…
Understanding Shared Speech-Text Representations
Gary Wang, Kyle Kastner, Ankur Bapna +4
Recently, a number of approaches to train speech models by incorpo-rating text into end-to-end models have been developed, with Mae-stro advancing state-of-the-art automatic speech…
Robust Knowledge Distillation from RNN-T Models With Noisy Training Labels Using Full-Sum Loss
Mohammad Zeineldeen, Kartik Audhkhasi, Murali Karthick Baskar +1
This work studies knowledge distillation (KD) and addresses its constraints for recurrent neural network transducer (RNN-T) models. In hard distillation, a teacher model transcribe…
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
Yu Zhang, Wei Han, James Qin +24
We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the enc…