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20222025
most citedSpeechX: Neural Codec Language Model as a Versatile Speech Transformer

3 citations · 4 across the 9 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

eess.AS2024

Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-to-Speech

Haibin Wu, Xiaofei Wang, Sefik Emre Eskimez +8

People change their tones of voice, often accompanied by nonverbal vocalizations (NVs) such as laughter and cries, to convey rich emotions. However, most text-to-speech (TTS) syste…

eess.AS2024

An Investigation of Noise Robustness for Flow-Matching-Based Zero-Shot TTS

Xiaofei Wang, Sefik Emre Eskimez, Manthan Thakker +8

Recently, zero-shot text-to-speech (TTS) systems, capable of synthesizing any speaker's voice from a short audio prompt, have made rapid advancements. However, the quality of the g…

eess.AS2024

Total-Duration-Aware Duration Modeling for Text-to-Speech Systems

Sefik Emre Eskimez, Xiaofei Wang, Manthan Thakker +9

Accurate control of the total duration of generated speech by adjusting the speech rate is crucial for various text-to-speech (TTS) applications. However, the impact of adjusting t…

eess.AS2024

E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS

Sefik Emre Eskimez, Xiaofei Wang, Manthan Thakker +10

This paper introduces Embarrassingly Easy Text-to-Speech (E2 TTS), a fully non-autoregressive zero-shot text-to-speech system that offers human-level naturalness and state-of-the-a…

eess.AS2024★ 1 cited

Making Flow-Matching-Based Zero-Shot Text-to-Speech Laugh as You Like

Naoyuki Kanda, Xiaofei Wang, Sefik Emre Eskimez +12

Laughter is one of the most expressive and natural aspects of human speech, conveying emotions, social cues, and humor. However, most text-to-speech (TTS) systems lack the ability…