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Found 56 papers, 9 papers with code
Multi-paraphrase Augmentation to Leverage Neural Caption Translation
In this paper, we investigate and utilize neural paraphrasing to improve translation quality in neural MT (NMT), which has not yet been much explored.
NAIST Simultaneous Speech-to-Text Translation System for IWSLT 2022
This paper describes NAIST’s simultaneous speech translation systems developed for IWSLT 2022 Evaluation Campaign.
NAIST English-to-Japanese Simultaneous Translation System for IWSLT 2021 Simultaneous Text-to-text Task
This paper describes NAIST’s system for the English-to-Japanese Simultaneous Text-to-text Translation Task in IWSLT 2021 Evaluation Campaign.
Using Spoken Word Posterior Features in Neural Machine Translation
In this paper, a neural sequence-to-sequence ASR is used as feature processing that is trained to produce word posterior features given spoken utterances.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
SpeeChain: A Speech Toolkit for Large-Scale Machine Speech Chain
This paper introduces SpeeChain, an open-source Pytorch-based toolkit designed to develop the machine speech chain for large-scale use.
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Instance-level Heterogeneous Domain Adaptation for Limited-labeled Sketch-to-Photo Retrieval
Therefore, previous works pre-train their models on rich-labeled photo retrieval data (i. e., source domain) and then fine-tune them on the limited-labeled sketch-to-photo retrieval data (i. e., target domain).
Ranked #1 on
Image Retrieval
on PKU-Reid
Actor-identified Spatiotemporal Action Detection --- Detecting Who Is Doing What in Videos
By using MOT, the spatiotemporal boundary of each actor is obtained and assigned to a unique actor identity.
Speech Artifact Removal from EEG Recordings of Spoken Word Production with Tensor Decomposition
Research about brain activities involving spoken word production is considerably underdeveloped because of the undiscovered characteristics of speech artifacts, which contaminate electroencephalogram (EEG) signals and prevent the inspection of the underlying cognitive processes.
Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing
The existing paradigm of semi-supervised S2S ASR utilizes SpecAugment as data augmentation and requires a static teacher model to produce pseudo transcripts for untranscribed speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Nix-TTS: Lightweight and End-to-End Text-to-Speech via Module-wise Distillation
We present Nix-TTS, a lightweight TTS achieved via knowledge distillation to a high-quality yet large-sized, non-autoregressive, and end-to-end (vocoder-free) TTS teacher model.
Simultaneous Speech-to-Speech Translation System with Neural Incremental ASR, MT, and TTS
This paper presents a newly developed, simultaneous neural speech-to-speech translation system and its evaluation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Cross-Lingual Machine Speech Chain for Javanese, Sundanese, Balinese, and Bataks Speech Recognition and Synthesis
We then develop ASR and TTS of ethnic languages by utilizing Indonesian ASR and TTS in a cross-lingual machine speech chain framework with only text or only speech data removing the need for paired speech-text data of those ethnic languages.
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework
Previous research has proposed a machine speech chain to enable automatic speech recognition (ASR) and text-to-speech synthesis (TTS) to assist each other in semi-supervised learning and to avoid the need for a large amount of paired speech and text data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Incremental Machine Speech Chain Towards Enabling Listening while Speaking in Real-time
By contrast, humans can listen to what hey speak in real-time, and if there is a delay in hearing, they won't be able to continue speaking.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Sequence-to-Sequence Learning via Attention Transfer for Incremental Speech Recognition
One main reason is because the model needs to decide the incremental steps and learn the transcription that aligns with the current short speech segment.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units
We present the Zero Resource Speech Challenge 2020, which aims at learning speech representations from raw audio signals without any labels.
ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentation
We aim to improve the performance of Multiple Object Tracking and Segmentation (MOTS) by refinement.
Ranked #1 on
Multi-Object Tracking
on MOTS20
Multi-Object Tracking
Multi-Object Tracking and Segmentation
+2
Transformer VQ-VAE for Unsupervised Unit Discovery and Speech Synthesis: ZeroSpeech 2020 Challenge
In this paper, we report our submitted system for the ZeroSpeech 2020 challenge on Track 2019.
Emotional Speech Corpus for Persuasive Dialogue System
Expressing emotion is known as an efficient way to persuade one{'}s dialogue partner to accept one{'}s claim or proposal.
Using Panoramic Videos for Multi-person Localization and Tracking in a 3D Panoramic Coordinate
3D panoramic multi-person localization and tracking are prominent in many applications, however, conventional methods using LiDAR equipment could be economically expensive and also computationally inefficient due to the processing of point cloud data.
Ranked #1 on
Multi-Object Tracking
on MOT15_3D
(using extra training data)
Speech-to-speech Translation between Untranscribed Unknown Languages
Second, we train a sequence-to-sequence model that directly maps the source language speech to the target language's discrete representation.
Make Skeleton-based Action Recognition Model Smaller, Faster and Better
Although skeleton-based action recognition has achieved great success in recent years, most of the existing methods may suffer from a large model size and slow execution speed.
Ranked #1 on
Hand Gesture Recognition
on DHG-14
Listening while Speaking and Visualizing: Improving ASR through Multimodal Chain
Previously, a machine speech chain, which is based on sequence-to-sequence deep learning, was proposed to mimic speech perception and production behavior.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
VQVAE Unsupervised Unit Discovery and Multi-scale Code2Spec Inverter for Zerospeech Challenge 2019
Our proposed approach significantly improved the intelligibility (in CER), the MOS, and discrimination ABX scores compared to the official ZeroSpeech 2019 baseline or even the topline.
The Zero Resource Speech Challenge 2019: TTS without T
We present the Zero Resource Speech Challenge 2019, which proposes to build a speech synthesizer without any text or phonetic labels: hence, TTS without T (text-to-speech without text).
End-to-End Feedback Loss in Speech Chain Framework via Straight-Through Estimator
In our previous work, we applied a speech chain mechanism as a semi-supervised learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Multi-scale Alignment and Contextual History for Attention Mechanism in Sequence-to-sequence Model
In this paper, we propose two ideas to improve sequence-to-sequence model performance by enhancing the attention module.
Unsupervised Counselor Dialogue Clustering for Positive Emotion Elicitation in Neural Dialogue System
Positive emotion elicitation seeks to improve user{'}s emotional state through dialogue system interaction, where a chat-based scenario is layered with an implicit goal to address user{'}s emotional needs.
Machine Speech Chain with One-shot Speaker Adaptation
In the speech chain loop mechanism, ASR also benefits from the ability to further learn an arbitrary speaker's characteristics from the generated speech waveform, resulting in a significant improvement in the recognition rate.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Tensor Decomposition for Compressing Recurrent Neural Network
In the machine learning fields, Recurrent Neural Network (RNN) has become a popular architecture for sequential data modeling.
Interactive Image Manipulation with Natural Language Instruction Commands
We propose an interactive image-manipulation system with natural language instruction, which can generate a target image from a source image and an instruction that describes the difference between the source and the target image.
Structured-based Curriculum Learning for End-to-end English-Japanese Speech Translation
Sequence-to-sequence attentional-based neural network architectures have been shown to provide a powerful model for machine translation and speech recognition.
Sequence-to-Sequence ASR Optimization via Reinforcement Learning
Despite the success of sequence-to-sequence approaches in automatic speech recognition (ASR) systems, the models still suffer from several problems, mainly due to the mismatch between the training and inference conditions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Attention-based Wav2Text with Feature Transfer Learning
In this paper, we construct the first end-to-end attention-based encoder-decoder model to process directly from raw speech waveform to the text transcription.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Listening while Speaking: Speech Chain by Deep Learning
In this paper, we take a step further and develop a closed-loop speech chain model based on deep learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Gated Recurrent Neural Tensor Network
Our proposed RNNs, which are called a Long-Short Term Memory Recurrent Neural Tensor Network (LSTMRNTN) and Gated Recurrent Unit Recurrent Neural Tensor Network (GRURNTN), are made by combining the LSTM and GRU RNN models with the tensor product.
Local Monotonic Attention Mechanism for End-to-End Speech and Language Processing
In this paper, we propose a novel attention mechanism that has local and monotonic properties.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Compressing Recurrent Neural Network with Tensor Train
Recurrent Neural Network (RNN) are a popular choice for modeling temporal and sequential tasks and achieve many state-of-the-art performance on various complex problems.
Construction of Japanese Audio-Visual Emotion Database and Its Application in Emotion Recognition
Emotional aspects play a vital role in making human communication a rich and dynamic experience.
Semantic Parsing of Ambiguous Input through Paraphrasing and Verification
We propose a new method for semantic parsing of ambiguous and ungrammatical input, such as search queries.
Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System
This paper outlines the recent development on multilingual medical data and multilingual speech recognition system for network-based speech-to-speech translation in the medical domain.
Collection of a Simultaneous Translation Corpus for Comparative Analysis
This makes it possible to compare translation data with simultaneous interpretation data.
