Survey on deep neural networks in speech and vision systems

M Alam, MD Samad, L Vidyaratne, A Glandon… - Neurocomputing, 2020 - Elsevier
This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …

Mixture of n-gram language models

H Sak, CGL Allauzen - US Patent 9,208,779, 2015 - Google Patents
BACKGROUND Speech recognition systems transcribe spoken words into text in a process
that is known as automatic speech recogni tion. Some speech recognition systems are …

[PDF][PDF] Accurate and compact large vocabulary speech recognition on mobile devices.

X Lei, AW Senior, A Gruenstein, J Sorensen - Interspeech, 2013 - research.google.com
In this paper we describe the development of an accurate, smallfootprint, large vocabulary
speech recognizer for mobile devices. To achieve the best recognition accuracy, state-of-the …

How do users respond to voice input errors? Lexical and phonetic query reformulation in voice search

J Jiang, W Jeng, D He - Proceedings of the 36th international ACM SIGIR …, 2013 - dl.acm.org
Voice search offers users with a new search experience: instead of typing, users can
vocalize their search queries. However, due to voice input errors (such as speech …

Acceptability of speech and silent speech input methods in private and public

L Pandey, K Hasan, AS Arif - Proceedings of the 2021 CHI Conference …, 2021 - dl.acm.org
Silent speech input converts non-acoustic features like tongue and lip movements into text. It
has been demonstrated as a promising input method on mobile devices and has been …

Speech recognition for mobile devices at Google

M Schuster - Pacific Rim International Conference on Artificial …, 2010 - Springer
LNAI 6230 - Speech Recognition for Mobile Devices at Google Page 1 Speech Recognition for
Mobile Devices at Google Mike Schuster Google Research, 1600 Amphitheatre Pkwy …

Speech2Health: a mobile framework for monitoring dietary composition from spoken data

N Hezarjaribi, S Mazrouee… - IEEE journal of …, 2017 - ieeexplore.ieee.org
Diet and physical activity are known as important lifestyle factors in self-management and
prevention of many chronic diseases. Mobile sensors such as accelerometers have been …

Contextual language model adaptation for conversational agents

A Raju, B Hedayatnia, L Liu, A Gandhe, C Khatri… - arXiv preprint arXiv …, 2018 - arxiv.org
Statistical language models (LM) play a key role in Automatic Speech Recognition (ASR)
systems used by conversational agents. These ASR systems should provide a high …

[PDF][PDF] Bayesian language model interpolation for mobile speech input

C Allauzen, M Riley - 2011 - isca-archive.org
This paper explores various static interpolation methods for approximating a single
dynamically-interpolated language model used for a variety of recognition tasks on the …

Proxitalk: Activate speech input by bringing smartphone to the mouth

Z Yang, C Yu, F Zheng, Y Shi - Proceedings of the ACM on Interactive …, 2019 - dl.acm.org
Speech input, such as voice assistant and voice message, is an attractive interaction option
for mobile users today. However, despite its popularity, there is a use limitation for …