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20192025
most citedUnsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Study

4 citations · 18 across the 25 of their papers we have counts for

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8 papers · 1 filter

eess.AS2025

ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech

Xin Wang, Héctor Delgado, Hemlata Tak +26

ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks as well as the design of detection solutions. We introduce…

eess.AS2024★ 1 cited

Text-To-Speech Synthesis In The Wild

Jee-weon Jung, Wangyou Zhang, Soumi Maiti +11

Traditional Text-to-Speech (TTS) systems rely on studio-quality speech recorded in controlled settings.a Recently, an effort known as noisy-TTS training has emerged, aiming to util…

eess.AS2024

SynesLM: A Unified Approach for Audio-visual Speech Recognition and Translation via Language Model and Synthetic Data

Yichen Lu, Jiaqi Song, Xuankai Chang +3

In this work, we present SynesLM, an unified model which can perform three multimodal language understanding tasks: audio-visual automatic speech recognition(AV-ASR) and visual-aid…

eess.AS2023

Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks

Soumi Maiti, Yifan Peng, Shukjae Choi +3

We propose a decoder-only language model, VoxtLM, that can perform four tasks: speech recognition, speech synthesis, text generation, and speech continuation. VoxtLM integrates tex…

eess.AS2023

Learning to Speak from Text: Zero-Shot Multilingual Text-to-Speech with Unsupervised Text Pretraining

Takaaki Saeki, Soumi Maiti, Xinjian Li +3

While neural text-to-speech (TTS) has achieved human-like natural synthetic speech, multilingual TTS systems are limited to resource-rich languages due to the need for paired text…

eess.AS2022★ 1 cited

SpeechLMScore: Evaluating speech generation using speech language model

Soumi Maiti, Yifan Peng, Takaaki Saeki +1

While human evaluation is the most reliable metric for evaluating speech generation systems, it is generally costly and time-consuming. Previous studies on automatic speech quality…

eess.AS2022★ 2 cited

EEND-SS: Joint End-to-End Neural Speaker Diarization and Speech Separation for Flexible Number of Speakers

Soumi Maiti, Yushi Ueda, Shinji Watanabe +4

In this paper, we present a novel framework that jointly performs three tasks: speaker diarization, speech separation, and speaker counting. Our proposed framework integrates speak…

eess.AS2019★ 4 cited

Speech denoising by parametric resynthesis

Soumi Maiti, Michael I Mandel

This work proposes the use of clean speech vocoder parameters as the target for a neural network performing speech enhancement. These parameters have been designed for text-to-spee…