Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview

• URL: http://arxiv.org/abs/2008.06580v2
• Date: Sun, 28 Feb 2021 19:41:45 GMT
• Title: Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview
• Authors: Peter Bell, Joachim Fainberg, Ondrej Klejch, Jinyu Li, Steve Renals, Pawel Swietojanski
• Abstract summary: We present a structured overview of adaptation algorithms for neural network-based speech recognition. The overview characterizes adaptation algorithms as based on embeddings, model parameter adaptation, or data augmentation. We present a meta-analysis of the performance of speech recognition adaptation algorithms, based on relative error rate reductions as reported in the literature.
• Score: 43.12352697785169
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a structured overview of adaptation algorithms for neural network-based speech recognition, considering both hybrid hidden Markov model / neural network systems and end-to-end neural network systems, with a focus on speaker adaptation, domain adaptation, and accent adaptation. The overview characterizes adaptation algorithms as based on embeddings, model parameter adaptation, or data augmentation. We present a meta-analysis of the performance of speech recognition adaptation algorithms, based on relative error rate reductions as reported in the literature.

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