Search Results for author: Takafumi Koshinaka

Found 7 papers, 0 papers with code

Unleashing the Unused Potential of I-Vectors Enabled by GPU Acceleration

no code implementations20 Jun 2019 Ville Vestman, Kong Aik Lee, Tomi H. Kinnunen, Takafumi Koshinaka

In particular, we achieve an acceleration of 3000 times in frame posterior computation compared to real time and 25 times in training the i-vector extractor compared to the CPU baseline from Kaldi toolkit.

Speaker Verification

Xi-Vector Embedding for Speaker Recognition

no code implementations12 Aug 2021 Kong Aik Lee, Qiongqiong Wang, Takafumi Koshinaka

We present a Bayesian formulation for deep speaker embedding, wherein the xi-vector is the Bayesian counterpart of the x-vector, taking into account the uncertainty estimate.

Speaker Recognition

Task-aware Warping Factors in Mask-based Speech Enhancement

no code implementations27 Aug 2021 Qiongqiong Wang, Kong Aik Lee, Takafumi Koshinaka, Koji Okabe, Hitoshi Yamamoto

It is easy to apply the proposed dual-warping factors approach to any mask-based SE method, and it allows a single SE system to handle multiple tasks without task-dependent training.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Image Captioners Sometimes Tell More Than Images They See

no code implementations4 May 2023 Honori Udo, Takafumi Koshinaka

We have evaluate several image captioning models with respect to a disaster image classification task, CrisisNLP, and show that descriptive text classifiers can sometimes achieve higher accuracy than standard image-based classifiers.

Descriptive Image Captioning +1

Generalized domain adaptation framework for parametric back-end in speaker recognition

no code implementations24 May 2023 Qiongqiong Wang, Koji Okabe, Kong Aik Lee, Takafumi Koshinaka

The efficacy of the proposed techniques has been experimentally validated on NIST 2016, 2018, and 2019 Speaker Recognition Evaluation (SRE'16, SRE'18, and SRE'19) datasets.

Speaker Recognition Unsupervised Domain Adaptation

Cannot find the paper you are looking for? You can Submit a new open access paper.