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09/19/2023
Multimodal Modeling For Spoken Language Identification
Spoken language identification refers to the task of automatically predi...
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09/09/2023
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
We introduce MADLAD-400, a manually audited, general domain 3T token mon...
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06/22/2023
AudioPaLM: A Large Language Model That Can Speak and Listen
We introduce AudioPaLM, a large language model for speech understanding ...
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06/07/2023
Label Aware Speech Representation Learning For Language Identification
Speech representation learning approaches for non-semantic tasks such as...
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05/30/2023
LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus
This paper introduces a new speech dataset called “LibriTTS-R” designed ...
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04/27/2023
Understanding Shared Speech-Text Representations
Recently, a number of approaches to train speech models by incorpo-ratin...
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03/03/2023
Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representations
Speech restoration (SR) is a task of converting degraded speech signals ...
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03/02/2023
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
We introduce the Universal Speech Model (USM), a single large model that...
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12/19/2022
Mu^2SLAM: Multitask, Multilingual Speech and Language Models
We present Mu^2SLAM, a multilingual sequence-to-sequence model pre-train...
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10/27/2022
Virtuoso: Massive Multilingual Speech-Text Joint Semi-Supervised Learning for Text-To-Speech
This paper proposes Virtuoso, a massively multilingual speech-text joint...
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10/18/2022
Maestro-U: Leveraging joint speech-text representation learning for zero supervised speech ASR
Training state-of-the-art Automated Speech Recognition (ASR) models typi...
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10/13/2022
JOIST: A Joint Speech and Text Streaming Model For ASR
We present JOIST, an algorithm to train a streaming, cascaded, encoder e...
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10/12/2022
SQuId: Measuring Speech Naturalness in Many Languages
Much of text-to-speech research relies on human evaluation, which incurs...
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05/25/2022
FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech
We introduce FLEURS, the Few-shot Learning Evaluation of Universal Repre...
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05/09/2022
Building Machine Translation Systems for the Next Thousand Languages
In this paper we share findings from our effort to build practical machi...
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04/07/2022
MAESTRO: Matched Speech Text Representations through Modality Matching
We present Maestro, a self-supervised training method to unify represent...
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03/24/2022
Leveraging unsupervised and weakly-supervised data to improve direct speech-to-speech translation
End-to-end speech-to-speech translation (S2ST) without relying on interm...
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03/21/2022
XTREME-S: Evaluating Cross-lingual Speech Representations
We introduce XTREME-S, a new benchmark to evaluate universal cross-lingu...
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03/15/2022
Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation
Multilingual neural machine translation models are trained to maximize t...
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02/03/2022
mSLAM: Massively multilingual joint pre-training for speech and text
We present mSLAM, a multilingual Speech and LAnguage Model that learns c...
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02/01/2022
Examining Scaling and Transfer of Language Model Architectures for Machine Translation
Natural language understanding and generation models follow one of the t...
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01/09/2022
Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning
Achieving universal translation between all human language pairs is the ...
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11/15/2021
Joint Unsupervised and Supervised Training for Multilingual ASR
Self-supervised training has shown promising gains in pretraining models...
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10/20/2021
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training
Unsupervised pre-training is now the predominant approach for both text ...
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09/21/2021
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents
Document-level neural machine translation (DocNMT) delivers coherent tra...
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09/16/2021
Scaling Laws for Neural Machine Translation
We present an empirical study of scaling properties of encoder-decoder T...
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03/22/2021
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
With the success of large-scale pre-training and multilingual modeling i...
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02/26/2021
Gradient-guided Loss Masking for Neural Machine Translation
To mitigate the negative effect of low quality training data on the perf...
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10/27/2020
Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus
Large text corpora are increasingly important for a wide variety of Natu...
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05/11/2020
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation
Over the last few years two promising research directions in low-resourc...
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02/17/2020
Controlling Computation versus Quality for Neural Sequence Models
Most neural networks utilize the same amount of compute for every exampl...
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01/14/2020
Faster Transformer Decoding: N-gram Masked Self-Attention
Motivated by the fact that most of the information relevant to the predi...
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10/30/2019
Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation
Most neural machine translation systems still translate sentences in iso...
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09/18/2019
Simple, Scalable Adaptation for Neural Machine Translation
Fine-tuning pre-trained Neural Machine Translation (NMT) models is the d...
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09/11/2019
Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model
Multilingual end-to-end (E2E) models have shown great promise in expansi...
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09/05/2019
Investigating Multilingual NMT Representations at Scale
Multilingual Neural Machine Translation (NMT) models have yielded large ...
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09/01/2019
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation
The recently proposed massively multilingual neural machine translation ...
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07/11/2019
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
We introduce our efforts towards building a universal neural machine tra...
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03/17/2019
The Missing Ingredient in Zero-Shot Neural Machine Translation
Multilingual Neural Machine Translation (NMT) models are capable of tran...
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02/28/2019
Non-Parametric Adaptation for Neural Machine Translation
Neural Networks trained with gradient descent are known to be susceptibl...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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08/29/2018
Revisiting Character-Based Neural Machine Translation with Capacity and Compression
Translating characters instead of words or word-fragments has the potent...
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08/22/2018
Training Deeper Neural Machine Translation Models with Transparent Attention
While current state-of-the-art NMT models, such as RNN seq2seq and Trans...
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04/26/2018
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
The past year has witnessed rapid advances in sequence-to-sequence (seq2...
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01/15/2018
Building a Conversational Agent Overnight with Dialogue Self-Play
We propose Machines Talking To Machines (M2M), a framework combining aut...
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07/07/2017
Towards Zero-Shot Frame Semantic Parsing for Domain Scaling
State-of-the-art slot filling models for goal-oriented human/machine con...
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05/08/2017
