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Found 15 papers, 4 papers with code
MSLM-S2ST: A Multitask Speech Language Model for Textless Speech-to-Speech Translation with Speaker Style Preservation
There have been emerging research interest and advances in speech-to-speech translation (S2ST), translating utterances from one language to another.
An Empirical Study of Speech Language Models for Prompt-Conditioned Speech Synthesis
Speech language models (LMs) are promising for high-quality speech synthesis through in-context learning.
Seamless: Multilingual Expressive and Streaming Speech Translation
In this work, we introduce a family of models that enable end-to-end expressive and multilingual translations in a streaming fashion.
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages?
Automatic Speech Recognition
Speech-to-Speech Translation
+3
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation
Maximum mean discrepancy (MMD) is a particularly useful distance metric for differentially private data generation: when used with finite-dimensional features it allows us to summarize and privatize the data distribution once, which we can repeatedly use during generator training without further privacy loss.
FeSAC: Federated Learning-Based Soft Actor-Critic Traffic Offloading in Space-Air-Ground Integrated Network
To further expand the resource pool of traffic offloading in SAGIN, we extend the single-layer satellite network into a double-layer satellite network composed of low-orbit satellites (LEO) and high-orbit satellites (GEO).
Speech-to-Speech Translation For A Real-world Unwritten Language
We use English-Taiwanese Hokkien as a case study, and present an end-to-end solution from training data collection, modeling choices to benchmark dataset release.
Sentiment Analysis of Covid-related Reddits
This paper focuses on Sentiment Analysis of Covid-19 related messages from the r/Canada and r/Unitedkingdom subreddits of Reddit.
Improving Multilingual Translation by Representation and Gradient Regularization
At the gradient level, we leverage a small amount of direct data (in thousands of sentence pairs) to regularize model gradients.
On the Sub-Layer Functionalities of Transformer Decoder
There have been significant efforts to interpret the encoder of Transformer-based encoder-decoder architectures for neural machine translation (NMT); meanwhile, the decoder remains largely unexamined despite its critical role.
Towards Frequency-Based Explanation for Robust CNN
We show that the vulnerability of the model against tiny distortions is a result of the model is relying on the high-frequency features, the target features of the adversarial (black and white-box) attackers, to make the prediction.
Software Engineering Practice in the Development of Deep Learning Applications
Specifically, we asked the respondents to identify lacks and challenges in the practice of the development life cycle of DL applications.
Software Engineering
Deep learning based mood tagging for Chinese song lyrics
Nowadays, listening music has been and will always be an indispensable part of our daily life.
Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System Report
This paper describes multimodal machine translation systems developed jointly by Oregon State University and Baidu Research for WMT 2018 Shared Task on multimodal translation.
Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation
Beam search is widely used in neural machine translation, and usually improves translation quality compared to greedy search.
