most citedUtilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Model

3 citations · 3 across the 5 of their papers we have counts for

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5 papers

eess.AS2024

Zero-shot Cross-lingual Voice Transfer for TTS

Fadi Biadsy, Youzheng Chen, Isaac Elias +4

In this paper, we introduce a zero-shot Voice Transfer (VT) module that can be seamlessly integrated into a multi-lingual Text-to-speech (TTS) system to transfer an individual's vo…

cs.SD2024

Adversarial training of Keyword Spotting to Minimize TTS Data Overfitting

Hyun Jin Park, Dhruuv Agarwal, Neng Chen +10

The keyword spotting (KWS) problem requires large amounts of real speech training data to achieve high accuracy across diverse populations. Utilizing large amounts of text-to-speec…

cs.SD2024★ 3 cited

Utilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Model

Hyun Jin Park, Dhruuv Agarwal, Neng Chen +10

This paper explores the use of TTS synthesized training data for KWS (keyword spotting) task while minimizing development cost and time. Keyword spotting models require a huge amou…

eess.AS2024

Extending Multilingual Speech Synthesis to 100+ Languages without Transcribed Data

Takaaki Saeki, Gary Wang, Nobuyuki Morioka +8

Collecting high-quality studio recordings of audio is challenging, which limits the language coverage of text-to-speech (TTS) systems. This paper proposes a framework for scaling a…

cs.CL2024

High-precision Voice Search Query Correction via Retrievable Speech-text Embedings

Christopher Li, Gary Wang, Kyle Kastner +9

Automatic speech recognition (ASR) systems can suffer from poor recall for various reasons, such as noisy audio, lack of sufficient training data, etc. Previous work has shown that…