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Found 42 papers, 8 papers with code
Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities
Conventional VC using shared context posterior probabilities predicts target speech parameters from the context posterior probabilities estimated from the source speech parameters.
Sampling-based speech parameter generation using moment-matching networks
To give synthetic speech natural inter-utterance variation, this paper builds DNN acoustic models that make it possible to randomly sample speech parameters.
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
In the proposed framework incorporating the GANs, the discriminator is trained to distinguish natural and generated speech parameters, while the acoustic models are trained to minimize the weighted sum of the conventional minimum generation loss and an adversarial loss for deceiving the discriminator.
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
Thanks to improvements in machine learning techniques including deep learning, a free large-scale speech corpus that can be shared between academic institutions and commercial companies has an important role.
Phase reconstruction from amplitude spectrograms based on von-Mises-distribution deep neural network
This paper presents a deep neural network (DNN)-based phase reconstruction from amplitude spectrograms.
Sound Audio and Speech Processing
Generative Moment Matching Network-based Random Modulation Post-filter for DNN-based Singing Voice Synthesis and Neural Double-tracking
To address this problem, we use a GMMN to model the variation of the modulation spectrum of the pitch contour of natural singing voices and add a randomized inter-utterance variation to the pitch contour generated by conventional DNN-based singing voice synthesis.
DNN-based Speaker Embedding Using Subjective Inter-speaker Similarity for Multi-speaker Modeling in Speech Synthesis
Although conventional DNN-based speaker embedding such as a $d$-vector can be applied to multi-speaker modeling in speech synthesis, it does not correlate with the subjective inter-speaker similarity and is not necessarily appropriate speaker representation for open speakers whose speech utterances are not included in the training data.
V2S attack: building DNN-based voice conversion from automatic speaker verification
The experimental evaluation compares converted voices between the proposed method that does not use the targeted speaker's voice data and the standard VC that uses the data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling
To model the human-acceptable distribution, we formulate a backpropagation-based generator training algorithm by regarding human perception as a black-boxed discriminator.
Time-Domain Audio Source Separation Based on Wave-U-Net Combined with Discrete Wavelet Transform
With this belief, focusing on the fact that the DWT has an anti-aliasing filter and the perfect reconstruction property, we design the proposed layers.
Utterance-level Sequential Modeling For Deep Gaussian Process Based Speech Synthesis Using Simple Recurrent Unit
This paper presents a deep Gaussian process (DGP) model with a recurrent architecture for speech sequence modeling.
DNN-based Speech Synthesis Using Abundant Tags of Spontaneous Speech Corpus
In this paper, we investigate the effectiveness of using rich annotations in deep neural network (DNN)-based statistical speech synthesis.
SMASH Corpus: A Spontaneous Speech Corpus Recording Third-person Audio Commentaries on Gameplay
Developing a spontaneous speech corpus would be beneficial for spoken language processing and understanding.
Multi-speaker Text-to-speech Synthesis Using Deep Gaussian Processes
We propose a framework for multi-speaker speech synthesis using deep Gaussian processes (DGPs); a DGP is a deep architecture of Bayesian kernel regressions and thus robust to overfitting.
HumanACGAN: conditional generative adversarial network with human-based auxiliary classifier and its evaluation in phoneme perception
A DNN-based generator is trained using a human-based discriminator, i. e., humans' perceptual evaluations, instead of the GAN's DNN-based discriminator.
Sampling-Frequency-Independent Audio Source Separation Using Convolution Layer Based on Impulse Invariant Method
Audio source separation is often used as preprocessing of various applications, and one of its ultimate goals is to construct a single versatile model capable of dealing with the varieties of audio signals.
Binaural rendering from microphone array signals of arbitrary geometry
To reproduce binaural signals from microphone array recordings at a remote location, a spherical microphone array is generally used for capturing a soundfield.
Low-Latency Incremental Text-to-Speech Synthesis with Distilled Context Prediction Network
Although this method achieves comparable speech quality to that of a method that waits for the future context, it entails a huge amount of processing for sampling from the language model at each time step.
Differentiable Digital Signal Processing Mixture Model for Synthesis Parameter Extraction from Mixture of Harmonic Sounds
A differentiable digital signal processing (DDSP) autoencoder is a musical sound synthesizer that combines a deep neural network (DNN) and spectral modeling synthesis.
Spatial active noise control based on individual kernel interpolation of primary and secondary sound fields
A spatial active noise control (ANC) method based on the individual kernel interpolation of primary and secondary sound fields is proposed.
STUDIES: Corpus of Japanese Empathetic Dialogue Speech Towards Friendly Voice Agent
We describe our methodology to construct an empathetic dialogue speech corpus and report the analysis results of the STUDIES corpus.
Region-to-region kernel interpolation of acoustic transfer function with directional weighting
A method of interpolating the acoustic transfer function (ATF) between regions that takes into account both the physical properties of the ATF and the directionality of region configurations is proposed.
Acoustic Modeling for End-to-End Empathetic Dialogue Speech Synthesis Using Linguistic and Prosodic Contexts of Dialogue History
To train the empathetic DSS model effectively, we investigate 1) a self-supervised learning model pretrained with large speech corpora, 2) a style-guided training using a prosody embedding of the current utterance to be predicted by the dialogue context embedding, 3) a cross-modal attention to combine text and speech modalities, and 4) a sentence-wise embedding to achieve fine-grained prosody modeling rather than utterance-wise modeling.
Human-in-the-loop Speaker Adaptation for DNN-based Multi-speaker TTS
With a conventional speaker-adaptation method, a target speaker's embedding vector is extracted from his/her reference speech using a speaker encoder trained on a speaker-discriminative task.
Multi-Task Adversarial Training Algorithm for Multi-Speaker Neural Text-to-Speech
A conventional generative adversarial network (GAN)-based training algorithm significantly improves the quality of synthetic speech by reducing the statistical difference between natural and synthetic speech.
Hyperbolic Timbre Embedding for Musical Instrument Sound Synthesis Based on Variational Autoencoders
In this paper, we propose a musical instrument sound synthesis (MISS) method based on a variational autoencoder (VAE) that has a hierarchy-inducing latent space for timbre.
Empirical Study Incorporating Linguistic Knowledge on Filled Pauses for Personalized Spontaneous Speech Synthesis
We present a comprehensive empirical study for personalized spontaneous speech synthesis on the basis of linguistic knowledge.
JaCappella Corpus: A Japanese a Cappella Vocal Ensemble Corpus
These songs were arranged from out-of-copyright Japanese children's songs and have six voice parts (lead vocal, soprano, alto, tenor, bass, and vocal percussion).
Ranked #1 on
Vocal ensemble separation
on jaCappella
Learning to Speak from Text: Zero-Shot Multilingual Text-to-Speech with Unsupervised Text Pretraining
While neural text-to-speech (TTS) has achieved human-like natural synthetic speech, multilingual TTS systems are limited to resource-rich languages due to the need for paired text and studio-quality audio data.
Duration-aware pause insertion using pre-trained language model for multi-speaker text-to-speech
We also leverage duration-aware pause insertion for more natural multi-speaker TTS.
Kernel interpolation of acoustic transfer functions with adaptive kernel for directed and residual reverberations
An interpolation method for region-to-region acoustic transfer functions (ATFs) based on kernel ridge regression with an adaptive kernel is proposed.
Spatial Active Noise Control Method Based On Sound Field Interpolation From Reference Microphone Signals
A spatial active noise control (ANC) method based on the interpolation of a sound field from reference microphone signals is proposed.
Kernel-interpolation-based spatial active noise control with exterior radiation suppression
A spatial active noise control (ANC) method based on kernel interpolation of a sound field with exterior radiation suppression is proposed.
ChatGPT-EDSS: Empathetic Dialogue Speech Synthesis Trained from ChatGPT-derived Context Word Embeddings
We focus on ChatGPT's reading comprehension and introduce it to EDSS, a task of synthesizing speech that can empathize with the interlocutor's emotion.
CALLS: Japanese Empathetic Dialogue Speech Corpus of Complaint Handling and Attentive Listening in Customer Center
We present CALLS, a Japanese speech corpus that considers phone calls in a customer center as a new domain of empathetic spoken dialogue.
How Generative Spoken Language Modeling Encodes Noisy Speech: Investigation from Phonetics to Syntactics
We examine the speech modeling potential of generative spoken language modeling (GSLM), which involves using learned symbols derived from data rather than phonemes for speech analysis and synthesis.
Multichannel Active Noise Control with Exterior Radiation Suppression Based on Riemannian Optimization
A multichannel active noise control (ANC) method with exterior radiation suppression is proposed.
Perceptual Quality Enhancement of Sound Field Synthesis Based on Combination of Pressure and Amplitude Matching
A sound field synthesis method enhancing perceptual quality is proposed.
Do learned speech symbols follow Zipf's law?
In this study, we investigate whether speech symbols, learned through deep learning, follow Zipf's law, akin to natural language symbols.
Localizing Acoustic Energy in Sound Field Synthesis by Directionally Weighted Exterior Radiation Suppression
A method for synthesizing the desired sound field while suppressing the exterior radiation power with directional weighting is proposed.
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis
Furthermore, we demonstrate that RALL-E correctly synthesizes sentences that are hard for VALL-E and reduces the error rate from $68\%$ to $4\%$.
