Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster

The Role of Disfluencies in Speech Translation

Current speech translation systems, including SpeechLLMs, are trained on cleaned text and tend to strip disfluencies like filled pauses and false starts rather than translate them. We show this comes at a cost: disfluencies carry meaning that gets lost when speech is cleaned up.

TTS Arena: Benchmarking Text-to-Speech Models in the Wild

Speech Synthesis, Recognition, and More With SpeechT5

MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task

arXiv:2606. 17255v1 Announce Type: cross Abstract: This work describes the participation of the MLLP-VRAIN research group in the shared task of the IWSLT 2026 Simultaneous Speech Translation track.

FormalASR: End-to-End Spoken Chinese to Formal Text

arXiv:2605. 19266v2 Announce Type: replace-cross Abstract: Automatic speech recognition (ASR) systems are typically optimized for verbatim transcription, which preserves disfluencies, filler words, and informal spoken structures that are often unsuitable for downstream writing-oriented applications.

CVSS-X: A Multilingual Speech-to-Speech Translation Corpus for 28 Languages

arXiv:2609.13413v1 Announce Type: new Abstract: We introduce CVSS-X, a large-scale synthetic speech-to-speech translation corpus that extends CVSS by reversing the translation direction. While CVSS t...