3 citations · 4 across the 10 of their papers we have counts for
11 papers
DLLM-TTS: Block Discrete Diffusion Language Model for Text-to-Speech Synthesis
Wasim Madha, Nityanand Mathur, Hamees Sayed +4
Current text-to-speech systems face a trade-off: autoregres- sive codec language models produce highly intelligible speech but require large-scale models and training data and deco…
Towards Operational Conversational Intelligence: A Speech Intelligence Framework
C. Vishnoi, S. Khurana, A. Timmapur +2
Body-worn camera (BWC) audio presents unique challenges including high ambient noise, variable recording conditions, and multiple overlapping speakers that make automated transcrip…
How Do Instructions Shape Speech? Cross-Attention Attribution for Style-Captioned Text-to-Speech
Nityanand Mathur, Hamees Sayed, Wasim Madha +4
Style-captioned text-to-speech systems use natural language to control voice characteristics, but how individual words influence acoustic output remains unclear. Understanding this…
Factorized RVQ-GAN For Disentangled Speech Tokenization
Sameer Khurana, Dominik Klement, Antoine Laurent +13
We propose Hierarchical Audio Codec (HAC), a unified neural speech codec that factorizes its bottleneck into three linguistic levels-acoustic, phonetic, and lexical-within a single…
HASRD: Hierarchical Acoustic and Semantic Representation Disentanglement
Amir Hussein, Sameer Khurana, Gordon Wichern +2
Effective speech representations for spoken language models must balance semantic relevance with acoustic fidelity for high-quality reconstruction. However, existing approaches str…
Leveraging Audio-Only Data for Text-Queried Target Sound Extraction
Kohei Saijo, Janek Ebbers, François G. Germain +3
The goal of text-queried target sound extraction (TSE) is to extract from a mixture a sound source specified with a natural-language caption. While it is preferable to have access…
SMITIN: Self-Monitored Inference-Time INtervention for Generative Music Transformers
Junghyun Koo, Gordon Wichern, Francois G. Germain +2
We introduce Self-Monitored Inference-Time INtervention (SMITIN), an approach for controlling an autoregressive generative music transformer using classifier probes. These simple l…
NIIRF: Neural IIR Filter Field for HRTF Upsampling and Personalization
Yoshiki Masuyama, Gordon Wichern, François G. Germain +4
Head-related transfer functions (HRTFs) are important for immersive audio, and their spatial interpolation has been studied to upsample finite measurements. Recently, neural fields…
NeuroHeed+: Improving Neuro-steered Speaker Extraction with Joint Auditory Attention Detection
Zexu Pan, Gordon Wichern, Francois G. Germain +2
Neuro-steered speaker extraction aims to extract the listener's brain-attended speech signal from a multi-talker speech signal, in which the attention is derived from the cortical…
Scenario-Aware Audio-Visual TF-GridNet for Target Speech Extraction
Zexu Pan, Gordon Wichern, Yoshiki Masuyama +4
Target speech extraction aims to extract, based on a given conditioning cue, a target speech signal that is corrupted by interfering sources, such as noise or competing speakers. B…
Generation or Replication: Auscultating Audio Latent Diffusion Models
Dimitrios Bralios, Gordon Wichern, François G. Germain +4
The introduction of audio latent diffusion models possessing the ability to generate realistic sound clips on demand from a text description has the potential to revolutionize how…