25 citations · 40 across the 24 of their papers we have counts for
9 papers · 1 filter
Prompt-Consistency Inference for Zero-Shot Flow-Matching Text-to-Speech Models
Vasily Zadorozhnyy, Can Goksen, Kazuhito Koishida +1
In recent years, flow-matching models have produced significant improvements in zero-shot text-to-speech synthesis. Conditioned on an audio prompt and text, these models learn a ve…
Zero-Shot Text-to-Speech from Continuous Text Streams
Trung Dang, David Aponte, Dung Tran +2
Existing zero-shot text-to-speech (TTS) systems are typically designed to process complete sentences and are constrained by the maximum duration for which they have been trained. H…
LiveSpeech: Low-Latency Zero-shot Text-to-Speech via Autoregressive Modeling of Audio Discrete Codes
Trung Dang, David Aponte, Dung Tran +1
Prior works have demonstrated zero-shot text-to-speech by using a generative language model on audio tokens obtained via a neural audio codec. It is still challenging, however, to…
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity
Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida +1
Conditional sound separation in multi-source audio mixtures without having access to single source sound data during training is a long standing challenge. Existing mix-and-separat…
uaMix-MAE: Efficient Tuning of Pretrained Audio Transformers with Unsupervised Audio Mixtures
Afrina Tabassum, Dung Tran, Trung Dang +2
Masked Autoencoders (MAEs) learn rich low-level representations from unlabeled data but require substantial labeled data to effectively adapt to downstream tasks. Conversely, Insta…
ConsistencyTTA: Accelerating Diffusion-Based Text-to-Audio Generation with Consistency Distillation
Yatong Bai, Trung Dang, Dung Tran +2
Diffusion models are instrumental in text-to-audio (TTA) generation. Unfortunately, they suffer from slow inference due to an excessive number of queries to the underlying denoisin…
SCP-GAN: Self-Correcting Discriminator Optimization for Training Consistency Preserving Metric GAN on Speech Enhancement Tasks
Vasily Zadorozhnyy, Qiang Ye, Kazuhito Koishida
In recent years, Generative Adversarial Networks (GANs) have produced significantly improved results in speech enhancement (SE) tasks. They are difficult to train, however. In this…
Training Robust Zero-Shot Voice Conversion Models with Self-supervised Features
Trung Dang, Dung Tran, Peter Chin +1
Unsupervised Zero-Shot Voice Conversion (VC) aims to modify the speaker characteristic of an utterance to match an unseen target speaker without relying on parallel training data.…
Interspeech 2021 Deep Noise Suppression Challenge
Chandan K A Reddy, Harishchandra Dubey, Kazuhito Koishida +7
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a…