94 citations · 292 across the 33 of their papers we have counts for
33 papers
Stereo Sound Event Localization and Detection with Onscreen/offscreen Classification
Kazuki Shimada, Archontis Politis, Iran R. Roman +10
This paper presents the objective, dataset, baseline, and metrics of Task 3 of the DCASE2025 Challenge on sound event localization and detection (SELD). In previous editions, the c…
LOCKEY: A Novel Approach to Model Authentication and Deepfake Tracking
Mayank Kumar Singh, Naoya Takahashi, Wei-Hsiang Liao +1
This paper presents a novel approach to deter unauthorized deepfakes and enable user tracking in generative models, even when the user has full access to the model parameters, by i…
SilentCipher: Deep Audio Watermarking
Mayank Kumar Singh, Naoya Takahashi, Weihsiang Liao +1
In the realm of audio watermarking, it is challenging to simultaneously encode imperceptible messages while enhancing the message capacity and robustness. Although recent advanceme…
STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events
Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam +9
While direction of arrival (DOA) of sound events is generally estimated from multichannel audio data recorded in a microphone array, sound events usually derive from visually perce…
Iteratively Improving Speech Recognition and Voice Conversion
Mayank Kumar Singh, Naoya Takahashi, Onoe Naoyuki
Many existing works on voice conversion (VC) tasks use automatic speech recognition (ASR) models for ensuring linguistic consistency between source and converted samples. However,…
The Whole Is Greater than the Sum of Its Parts: Improving Music Source Separation by Bridging Network
Ryosuke Sawata, Naoya Takahashi, Stefan Uhlich +2
This paper presents the crossing scheme (X-scheme) for improving the performance of deep neural network (DNN)-based music source separation (MSS) with almost no increasing calculat…
Cross-modal Face- and Voice-style Transfer
Naoya Takahashi, Mayank K. Singh, Yuki Mitsufuji
Image-to-image translation and voice conversion enable the generation of a new facial image and voice while maintaining some of the semantics such as a pose in an image and linguis…
Nonparallel Emotional Voice Conversion For Unseen Speaker-Emotion Pairs Using Dual Domain Adversarial Network & Virtual Domain Pairing
Nirmesh Shah, Mayank Kumar Singh, Naoya Takahashi +1
Primary goal of an emotional voice conversion (EVC) system is to convert the emotion of a given speech signal from one style to another style without modifying the linguistic conte…
CLIPSep: Learning Text-queried Sound Separation with Noisy Unlabeled Videos
Hao-Wen Dong, Naoya Takahashi, Yuki Mitsufuji +2
Recent years have seen progress beyond domain-specific sound separation for speech or music towards universal sound separation for arbitrary sounds. Prior work on universal sound s…
DiffRoll: Diffusion-based Generative Music Transcription with Unsupervised Pretraining Capability
Kin Wai Cheuk, Ryosuke Sawata, Toshimitsu Uesaka +5
In this paper we propose a novel generative approach, DiffRoll, to tackle automatic music transcription (AMT). Instead of treating AMT as a discriminative task in which the model i…
Hierarchical Diffusion Models for Singing Voice Neural Vocoder
Naoya Takahashi, Mayank Kumar, Singh +1
Recent progress in deep generative models has improved the quality of neural vocoders in speech domain. However, generating a high-quality singing voice remains challenging due to…
Robust One-Shot Singing Voice Conversion
Naoya Takahashi, Mayank Kumar Singh, Yuki Mitsufuji
Recent progress in deep generative models has improved the quality of voice conversion in the speech domain. However, high-quality singing voice conversion (SVC) of unseen singers…
Leveraging Symmetrical Convolutional Transformer Networks for Speech to Singing Voice Style Transfer
Shrutina Agarwal, Sriram Ganapathy, Naoya Takahashi
In this paper, we propose a model to perform style transfer of speech to singing voice. Contrary to the previous signal processing-based methods, which require high-quality singing…
STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events
Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam +7
This report presents the Sony-TAu Realistic Spatial Soundscapes 2022 (STARS22) dataset for sound event localization and detection, comprised of spatial recordings of real scenes co…
Multi-ACCDOA: Localizing and Detecting Overlapping Sounds from the Same Class with Auxiliary Duplicating Permutation Invariant Training
Kazuki Shimada, Yuichiro Koyama, Shusuke Takahashi +3
Sound event localization and detection (SELD) involves identifying the direction-of-arrival (DOA) and the event class. The SELD methods with a class-wise output format make the mod…
Spatial Data Augmentation with Simulated Room Impulse Responses for Sound Event Localization and Detection
Yuichiro Koyama, Kazuhide Shigemi, Masafumi Takahashi +5
Recording and annotating real sound events for a sound event localization and detection (SELD) task is time consuming, and data augmentation techniques are often favored when the a…
Amicable examples for informed source separation
Naoya Takahashi, Yuki Mitsufuji
This paper deals with the problem of informed source separation (ISS), where the sources are accessible during the so-called \textit{encoding} stage. Previous works computed side-i…
Source Mixing and Separation Robust Audio Steganography
Naoya Takahashi, Mayank Kumar Singh, Yuki Mitsufuji
Audio steganography aims at concealing secret information in carrier audio with imperceptible modification on the carrier. Although previous works addressed the robustness of conce…
Ensemble of ACCDOA- and EINV2-based Systems with D3Nets and Impulse Response Simulation for Sound Event Localization and Detection
Kazuki Shimada, Naoya Takahashi, Yuichiro Koyama +4
This report describes our systems submitted to the DCASE2021 challenge task 3: sound event localization and detection (SELD) with directional interference. Our previous system base…
End-to-end lyrics Recognition with Voice to Singing Style Transfer
Sakya Basak, Shrutina Agarwal, Sriram Ganapathy +1
Automatic transcription of monophonic/polyphonic music is a challenging task due to the lack of availability of large amounts of transcribed data. In this paper, we propose a data…
Hierarchical disentangled representation learning for singing voice conversion
Naoya Takahashi, Mayank Kumar Singh, Yuki Mitsufuji
Conventional singing voice conversion (SVC) methods often suffer from operating in high-resolution audio owing to a high dimensionality of data. In this paper, we propose a hierarc…
Densely connected multidilated convolutional networks for dense prediction tasks
Naoya Takahashi, Yuki Mitsufuji
Tasks that involve high-resolution dense prediction require a modeling of both local and global patterns in a large input field. Although the local and global structures often depe…
ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection
Kazuki Shimada, Yuichiro Koyama, Naoya Takahashi +2
Neural-network (NN)-based methods show high performance in sound event localization and detection (SELD). Conventional NN-based methods use two branches for a sound event detection…
Adversarial attacks on audio source separation
Naoya Takahashi, Shota Inoue, Yuki Mitsufuji
Despite the excellent performance of neural-network-based audio source separation methods and their wide range of applications, their robustness against intentional attacks has bee…