8 accepted papers
Recent advances in video multimodal large language models (Video MLLMs) have significantly enhanced video understanding and multi-modal interaction capabilities. While most existing systems operate in a turn-based manner where the model can only reply after user turns, proactively deciding when to r…
Dysarthric speech reconstruction (DSR) aims to transform dysarthric speech into normal speech by improving the intelligibility and naturalness. This is a challenging task especially for patients with severe dysarthria and speaking in complex, noisy acoustic environments. To address these challenges,…
Dysarthric speech reconstruction (DSR) systems aim to automatically convert dysarthric speech into normal-sounding speech. The technology eases communication with speakers affected by the neuromotor disorder and enhances their social inclusion. NED-based (Neural Encoder-Decoder) systems have signifi…
Dysarthric speech reconstruction (DSR), which aims to improve the quality of dysarthric speech, remains a challenge, not only because we need to restore the speech to be normal, but also must preserve the speaker’s identity. The speaker representation extracted by the speaker encoder (SE) optimized…
Though significant progress has been made for speaker-dependent Video-to-Speech (VTS) synthesis, little attention is devoted to multi-speaker VTS that can map silent video to speech, while allowing flexible control of speaker identity, all in a single system. This paper proposes a novel multi-speake…
Sequence-to-sequence (seq2seq) learning has greatly improved text-to-speech (TTS) synthesis performance, but effective implementation on resource-restricted devices remains challenging as seq2seq models are usually computationally expensive and memory intensive. To achieve fast inference speed and s…
Techniques for accent conversion (AC) aim to convert non-native to native accented speech. Conventional AC methods try to convert only the speaker identity of a native speaker's voice to that of the non-native accented target speaker, leaving the underlying content and pronunciations unchanged. This…
Dysarthric speech reconstruction (DSR) is a challenging task due to difficulties in repairing unstable prosody and correcting imprecise articulation. Inspired by the success of sequence-to-sequence (seq2seq) based text-to-speech (TTS) synthesis and knowledge distillation (KD) techniques, this paper…