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Abhinav Garg

3 accepted papers

2024

Data Driven Grapheme-to-Phoneme Representations for a Lexicon-Free Text-to-Speech

ICASSP 2024accepted

Grapheme-to-Phoneme (G2P) is an essential first step in any modern, high-quality Text-to-Speech (TTS) system. Most of the current G2P systems rely on carefully hand-crafted lexicons developed by experts. This poses a two-fold problem. Firstly, the lexicons are generated using a fixed phoneme set, us…

Cited by 0SourceScholar
2023

Self-Supervised Accent Learning for Under-Resourced Accents Using Native Language Data

ICASSP 2023accepted

In this paper, we propose a novel method to improve the accuracy of an English speech recognizer for a target accent using the corresponding native language data. Collecting labeled data for all accents of English to train an end-to-end neural speech recognizer for English is a difficult and expensi…

Cited by 0SourceScholar
2021

Streaming End-to-End Speech Recognition with Jointly Trained Neural Feature Enhancement

ICASSP 2021accepted

In this paper, we present a streaming end-to-end speech recognition model based on Monotonic Chunkwise Attention (MoCha) jointly trained with enhancement layers. Even though the MoCha attention enables streaming speech recognition with recognition accuracy comparable to a full attention-based approa…

Cited by 0SourceScholar