Speech Recognition

Self-supervised speech foundation models are now used in a wide array of downstream applications, including traditional speech recognition and as the basis for tokens in speech-aware language models. Attempts to understa…

Speech Recognition

Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services

2026-09-09 · Yonghyun Jun, Jimin Lee, Hwan Chang, Dongho Shin 외 arxiv

Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR models exhibit inevitable errors in complex real-world environments su…

Speech Recognition

$S^3$-Bench: Evaluating Speech Interaction Models as Scientific Voice Assistants

2026-09-09 · Heyang Liu, Jiayi Huang, Wenyang Xiao, Ziyang Cheng 외 arxiv

The advance of multimodal large language models (MLLMs) has fundamentally reshaped the paradigm of human-computer interaction, especially speech interaction models capable of seamless conversations. Despite remarkable pe…

Speech Recognition

StreamAlign: Streaming Text-Aligned Speech Tokenization

2026-09-09 · Kang-wook Kim, Jinyoung Park, Jinsoo Kim, Sehun Lee 외 arxiv

Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretrained LLMs. However, they rely on offline automatic speech recognitio…

Speech Recognition

SEA-SpeechBench: A Large-Scale Multitask Benchmark for Speech Understanding Across Southeast Asia

2026-09-09 · Jingyi Liao, Wenyu Zhang, Zhuohan Liu, Yingxu He 외 arxiv

The rapid advancement of audio and multimodal large language models has unlocked transformative speech understanding capabilities, yet evaluation frameworks remain predominantly English-centric, leaving Southeast Asian (…

Emotion Recognition Speaker Recognition Speech Recognition Question Answering

Qwen-Audio-3.0-ASR Technical Report

2026-09-07 · Chuanmeng Bian, Daren Chen, Peixin Chen, Zhigao Chen 외 arxiv

In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling, model scaling, and deep integration with large language models (LLMs). …

Speech Recognition

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