88 citations · 308 across the 88 of their papers we have counts for
64 papers · 1 filter
Spatial Voice Conversion: Voice Conversion Preserving Spatial Information and Non-target Signals
Kentaro Seki, Shinnosuke Takamichi, Norihiro Takamune +3
This paper proposes a new task called spatial voice conversion, which aims to convert a target voice while preserving spatial information and non-target signals. Traditional voice…
Noise-Robust Voice Conversion by Conditional Denoising Training Using Latent Variables of Recording Quality and Environment
Takuto Igarashi, Yuki Saito, Kentaro Seki +4
We propose noise-robust voice conversion (VC) which takes into account the recording quality and environment of noisy source speech. Conventional denoising training improves the no…
SRC4VC: Smartphone-Recorded Corpus for Voice Conversion Benchmark
Yuki Saito, Takuto Igarashi, Kentaro Seki +4
We present SRC4VC, a new corpus containing 11 hours of speech recorded on smartphones by 100 Japanese speakers. Although high-quality multi-speaker corpora can advance voice conver…
Building speech corpus with diverse voice characteristics for its prompt-based representation
Aya Watanabe, Shinnosuke Takamichi, Yuki Saito +3
In text-to-speech synthesis, the ability to control voice characteristics is vital for various applications. By leveraging thriving text prompt-based generation techniques, it shou…
Real-time Speech Extraction Using Spatially Regularized Independent Low-rank Matrix Analysis and Rank-constrained Spatial Covariance Matrix Estimation
Yuto Ishikawa, Kohei Konaka, Tomohiko Nakamura +2
Real-time speech extraction is an important challenge with various applications such as speech recognition in a human-like avatar/robot. In this paper, we propose the real-time ext…
SpeechBERTScore: Reference-Aware Automatic Evaluation of Speech Generation Leveraging NLP Evaluation Metrics
Takaaki Saeki, Soumi Maiti, Shinnosuke Takamichi +2
While subjective assessments have been the gold standard for evaluating speech generation, there is a growing need for objective metrics that are highly correlated with human subje…
JVNV: A Corpus of Japanese Emotional Speech with Verbal Content and Nonverbal Expressions
Detai Xin, Junfeng Jiang, Shinnosuke Takamichi +3
We present the JVNV, a Japanese emotional speech corpus with verbal content and nonverbal vocalizations whose scripts are generated by a large-scale language model. Existing emotio…
Coco-Nut: Corpus of Japanese Utterance and Voice Characteristics Description for Prompt-based Control
Aya Watanabe, Shinnosuke Takamichi, Yuki Saito +3
In text-to-speech, controlling voice characteristics is important in achieving various-purpose speech synthesis. Considering the success of text-conditioned generation, such as tex…
Diversity-based core-set selection for text-to-speech with linguistic and acoustic features
Kentaro Seki, Shinnosuke Takamichi, Takaaki Saeki +1
This paper proposes a method for extracting a lightweight subset from a text-to-speech (TTS) corpus ensuring synthetic speech quality. In recent years, methods have been proposed f…
NoisyILRMA: Diffuse-Noise-Aware Independent Low-Rank Matrix Analysis for Fast Blind Source Extraction
Koki Nishida, Norihiro Takamune, Rintaro Ikeshita +3
In this paper, we address the multichannel blind source extraction (BSE) of a single source in diffuse noise environments. To solve this problem even faster than by fast multichann…
Algorithms of Sampling-Frequency-Independent Layers for Non-integer Strides
Kanami Imamura, Tomohiko Nakamura, Norihiro Takamune +2
In this paper, we propose algorithms for handling non-integer strides in sampling-frequency-independent (SFI) convolutional and transposed convolutional layers. The SFI layers have…
Laughter Synthesis using Pseudo Phonetic Tokens with a Large-scale In-the-wild Laughter Corpus
Detai Xin, Shinnosuke Takamichi, Ai Morimatsu +1
We present a large-scale in-the-wild Japanese laughter corpus and a laughter synthesis method. Previous work on laughter synthesis lacks not only data but also proper ways to repre…
ChatGPT-EDSS: Empathetic Dialogue Speech Synthesis Trained from ChatGPT-derived Context Word Embeddings
Yuki Saito, Shinnosuke Takamichi, Eiji Iimori +2
We propose ChatGPT-EDSS, an empathetic dialogue speech synthesis (EDSS) method using ChatGPT for extracting dialogue context. ChatGPT is a chatbot that can deeply understand the co…
CALLS: Japanese Empathetic Dialogue Speech Corpus of Complaint Handling and Attentive Listening in Customer Center
Yuki Saito, Eiji Iimori, Shinnosuke Takamichi +2
We present CALLS, a Japanese speech corpus that considers phone calls in a customer center as a new domain of empathetic spoken dialogue. The existing STUDIES corpus covers only em…
JNV Corpus: A Corpus of Japanese Nonverbal Vocalizations with Diverse Phrases and Emotions
Detai Xin, Shinnosuke Takamichi, Hiroshi Saruwatari
We present JNV (Japanese Nonverbal Vocalizations) corpus, a corpus of Japanese nonverbal vocalizations (NVs) with diverse phrases and emotions. Existing Japanese NV corpora lack ph…
Improving Speech Prosody of Audiobook Text-to-Speech Synthesis with Acoustic and Textual Contexts
Detai Xin, Sharath Adavanne, Federico Ang +3
We present a multi-speaker Japanese audiobook text-to-speech (TTS) system that leverages multimodal context information of preceding acoustic context and bilateral textual context…
Text-to-speech synthesis from dark data with evaluation-in-the-loop data selection
Kentaro Seki, Shinnosuke Takamichi, Takaaki Saeki +1
This paper proposes a method for selecting training data for text-to-speech (TTS) synthesis from dark data. TTS models are typically trained on high-quality speech corpora that cos…
Mid-attribute speaker generation using optimal-transport-based interpolation of Gaussian mixture models
Aya Watanabe, Shinnosuke Takamichi, Yuki Saito +2
In this paper, we propose a method for intermediating multiple speakers' attributes and diversifying their voice characteristics in ``speaker generation,'' an emerging task that ai…
Visual onoma-to-wave: environmental sound synthesis from visual onomatopoeias and sound-source images
Hien Ohnaka, Shinnosuke Takamichi, Keisuke Imoto +3
We propose a method for synthesizing environmental sounds from visually represented onomatopoeias and sound sources. An onomatopoeia is a word that imitates a sound structure, i.e.…
Improving robustness of spontaneous speech synthesis with linguistic speech regularization and pseudo-filled-pause insertion
Yuta Matsunaga, Takaaki Saeki, Shinnosuke Takamichi +1
We present a training method with linguistic speech regularization that improves the robustness of spontaneous speech synthesis methods with filled pause (FP) insertion. Spontaneou…
Empirical Study Incorporating Linguistic Knowledge on Filled Pauses for Personalized Spontaneous Speech Synthesis
Yuta Matsunaga, Takaaki Saeki, Shinnosuke Takamichi +1
We present a comprehensive empirical study for personalized spontaneous speech synthesis on the basis of linguistic knowledge. With the advent of voice cloning for reading-style sp…
Multi-Task Adversarial Training Algorithm for Multi-Speaker Neural Text-to-Speech
Yusuke Nakai, Yuki Saito, Kenta Udagawa +1
We propose a novel training algorithm for a multi-speaker neural text-to-speech (TTS) model based on multi-task adversarial training. A conventional generative adversarial network…
Head-Related Transfer Function Interpolation from Spatially Sparse Measurements Using Autoencoder with Source Position Conditioning
Yuki Ito, Tomohiko Nakamura, Shoichi Koyama +1
We propose a method of head-related transfer function (HRTF) interpolation from sparsely measured HRTFs using an autoencoder with source position conditioning. The proposed method…
Physics-informed convolutional neural network with bicubic spline interpolation for sound field estimation
Kazuhide Shigemi, Shoichi Koyama, Tomohiko Nakamura +1
A sound field estimation method based on a physics-informed convolutional neural network (PICNN) using spline interpolation is proposed. Most of the sound field estimation methods…