activity
20212026
most citedZero-shot text-to-speech synthesis conditioned using self-supervised speech representation model

9 citations · 24 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

13 papers · 1 filter

cs.SD2024

Investigation of Speaker Representation for Target-Speaker Speech Processing

Takanori Ashihara, Takafumi Moriya, Shota Horiguchi +5

Target-speaker speech processing (TS) tasks, such as target-speaker automatic speech recognition (TS-ASR), target speech extraction (TSE), and personal voice activity detection (p-…

eess.AS2024★ 1 cited

Guided Speaker Embedding

Shota Horiguchi, Takafumi Moriya, Atsushi Ando +4

This paper proposes a guided speaker embedding extraction system, which extracts speaker embeddings of the target speaker using speech activities of target and interference speaker…

eess.AS2024

Boosting Hybrid Autoregressive Transducer-based ASR with Internal Acoustic Model Training and Dual Blank Thresholding

Takafumi Moriya, Takanori Ashihara, Masato Mimura +4

A hybrid autoregressive transducer (HAT) is a variant of neural transducer that models blank and non-blank posterior distributions separately. In this paper, we propose a novel int…

eess.AS2024

Alignment-Free Training for Transducer-based Multi-Talker ASR

Takafumi Moriya, Shota Horiguchi, Marc Delcroix +5

Extending the RNN Transducer (RNNT) to recognize multi-talker speech is essential for wider automatic speech recognition (ASR) applications. Multi-talker RNNT (MT-RNNT) aims to ach…

eess.AS2024

NTT Multi-Speaker ASR System for the DASR Task of CHiME-8 Challenge

Naoyuki Kamo, Naohiro Tawara, Atsushi Ando +15

We present a distant automatic speech recognition (DASR) system developed for the CHiME-8 DASR track. It consists of a diarization first pipeline. For diarization, we use end-to-en…

eess.AS2024

Recursive Attentive Pooling for Extracting Speaker Embeddings from Multi-Speaker Recordings

Shota Horiguchi, Atsushi Ando, Takafumi Moriya +4

This paper proposes a method for extracting speaker embedding for each speaker from a variable-length recording containing multiple speakers. Speaker embeddings are crucial not onl…

cs.CL2024

Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation

Kohei Matsuura, Takanori Ashihara, Takafumi Moriya +4

This paper introduces a novel approach called sentence-wise speech summarization (Sen-SSum), which generates text summaries from a spoken document in a sentence-by-sentence manner.…

eess.AS2024

SpeakerBeam-SS: Real-time Target Speaker Extraction with Lightweight Conv-TasNet and State Space Modeling

Hiroshi Sato, Takafumi Moriya, Masato Mimura +6

Real-time target speaker extraction (TSE) is intended to extract the desired speaker's voice from the observed mixture of multiple speakers in a streaming manner. Implementing real…

cs.SD2024

Lightweight Zero-shot Text-to-Speech with Mixture of Adapters

Kenichi Fujita, Takanori Ashihara, Marc Delcroix +1

The advancements in zero-shot text-to-speech (TTS) methods, based on large-scale models, have demonstrated high fidelity in reproducing speaker characteristics. However, these mode…

eess.AS2024★ 2 cited

Applying LLMs for Rescoring N-best ASR Hypotheses of Casual Conversations: Effects of Domain Adaptation and Context Carry-over

Atsunori Ogawa, Naoyuki Kamo, Kohei Matsuura +5

Large language models (LLMs) have been successfully applied for rescoring automatic speech recognition (ASR) hypotheses. However, their ability to rescore ASR hypotheses of casual…

eess.AS2024

Probing Self-supervised Learning Models with Target Speech Extraction

Junyi Peng, Marc Delcroix, Tsubasa Ochiai +4

Large-scale pre-trained self-supervised learning (SSL) models have shown remarkable advancements in speech-related tasks. However, the utilization of these models in complex multi-…

cs.CL2024

What Do Self-Supervised Speech and Speaker Models Learn? New Findings From a Cross Model Layer-Wise Analysis

Takanori Ashihara, Marc Delcroix, Takafumi Moriya +3

Self-supervised learning (SSL) has attracted increased attention for learning meaningful speech representations. Speech SSL models, such as WavLM, employ masked prediction training…

cs.SD2024

Noise-robust zero-shot text-to-speech synthesis conditioned on self-supervised speech-representation model with adapters

Kenichi Fujita, Hiroshi Sato, Takanori Ashihara +4

The zero-shot text-to-speech (TTS) method, based on speaker embeddings extracted from reference speech using self-supervised learning (SSL) speech representations, can reproduce sp…