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~ similar to 2606.24320· 14 results

cs.CLcs.AIeess.ASRecentMay 31, 2026

PolySpeech-100: A Large-Scale Benchmark for Speech Understanding Across 100+ Languages and Dialects

Sicheng Yang, Shulan Ruan, Shiwei Wu, Yu Liu +3 more

PolySpeech-100 introduces a massive, multi-lingual benchmark covering 110 linguistic variants to rigorously test Speech-LLMs, demonstrating that open-source models struggle with low-resource languages…

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cs.LGcs.SDEmpiricalRecentJul 24, 2026

Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning

Roseline Polle, Owen Parsons, George Fairs, Luis Miguel San Martin Fernandez +4 more

Eight voice cloning models are benchmarked on five paralinguistic tasks, showing most preserve signal with modest degradation. Cloning English clinical speech into Japanese outperforms raw cross-lingu…

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eess.ASEmpiricalRecentJun 27, 2026

GigaSpeechBench: A Real-World Multilingual Speech-to-Text Benchmark

Yujie Tu, Yifan Yang, Tianrui Wang, Yanqiao Zhu +32 more

The paper introduces GigaSpeechBench, a comprehensive multilingual and multidimensional ASR & AST benchmark with 680 hours of human-annotated speech, featuring 12 low-resource languages, 6 Chinese dia…

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eess.ASEmpiricalRecentJul 25, 2026

Singlish, Can or Not? Fine-Tuning and Evaluating Zero-Shot TTS for Singapore English

Ivan Kukanov, Zheng Xin Chai

This paper fine-tunes two zero-shot text-to-speech models, Chatterbox and CosyVoice 3, on Singlish speakers from the IMDA National Speech Corpus to improve accent similarity and naturalness.

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cs.CLcs.AIeess.ASEmpiricalRecentJul 6, 2026

SPEARBench: A Benchmark for Naturalness Evaluation in Streaming Speech-to-Speech Language Models

Thomas Thebaud, Yuzhe Wang, Hao Zhang, Sathvik Manikantan Napa Ugandhar +4 more

The paper introduces SPEARBench, a benchmark for evaluating naturalness in speech-to-speech language models using a multidimensional protocol.

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eess.ASDatasetRecentJul 15, 2026

Dialogs: a studio-quality expressive conversational Russian speech corpus for dialog assistants

Ilya Shigabeev, Ilya Latyshev

The paper introduces Dialogs, a new Russian conversational speech corpus with high-quality recordings, segmented utterances, and expressive prosody labels.

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cs.CLcs.AIcs.SDRecentMay 29, 2026

Scaling Conversational Hungarian ASR: The BEA-Dialogue+ Corpus

Máté Gedeon, Piroska Zsófia Barta, Péter Mihajlik, Katalin Mády

The paper introduces BEA-Dialogue+, an expanded 200-hour corpus for Hungarian conversational ASR, demonstrating that while larger data is challenging, specialized fine-tuning techniques significantly…

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eess.ASEmpiricalRecentJun 18, 2026

Transcript-Free Flow-Matching Text-to-Speech via Speech Feature Conditioning

SooHwan Eom, Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson +1 more

The paper proposes RTFree-F5, a method to make flow-matching TTS models like F5-TTS independent of reference transcripts, improving performance and naturalness for dysarthric speakers.

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eess.AScs.AIRecentMay 29, 2026

OpenSTBench: Beyond Semantic Evaluation for Speech Translation

Yanjie An, Yuxiang Zhao, Yichi Zhang, Qixi Zheng +4 more

The paper introduces OpenSTBench, a unified, multidimensional evaluation framework designed to comprehensively compare heterogeneous speech translation systems by jointly assessing translation, speech…

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eess.ASEmpiricalRecentJul 20, 2026

X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System

Yuxiang Zhao, Yichi Zhang, Yanjie An, Yanqiao Zhu +9 more

X-Translator is a low-cost modular system for real-time speech-to-speech translation, using streaming ASR, machine translation, and prompt-conditioned TTS, with session-level control.

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eess.ASEmpiricalRecentJun 16, 2026

An Analysis of the Effectiveness of Synthetic Speech Data for ASR Fine-tuning in Selected Indic Languages

Sujith Pulikodan, Agneedh Basu, Pavan Kumar, Pranav Bhat +3 more

This paper investigates the effectiveness of incorporating synthetic speech data in Automatic Speech Recognition (ASR) Systems for three Indic languages by analyzing performance gains, script sources,…

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eess.AScs.SDEmpiricalRecentJul 28, 2026

Extracting Voice Styles from Frozen TTS Models via Gradient-Based Inverse Optimization

Gyeongmin Kim

The paper describes a method to optimize the style vector for text-to-speech systems without a reference encoder, improving similarity and acceptance rate.

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