Multichannel speech recognition using distributed microphone signal fusion strategies

Trawicki, Marek B.; Johnson, Michael T.; Ji, An; Osiejuk, Tomasz S.

doi:10.1109/icalip.2012.6376789

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…Some NUI, especially gesture NUIs are criticised as artificial naturality since they replace tangible interface (Hyoung et al 2013;Hong et al 2011;Ishikawa and Saito 2008;Miu-Ling et al 2015) 1. Ambient sound capture with speech recognition (Trawicki et al 2012;Giannoulis et al 2015;Soda et al 2013;Ishi et al 2015) Capturing of 3D images with facial and body parts details must be done when the subject person is still alive for a computer graphics to simulate real time body movement on a 3D display. Pre-defined questions and answers are also recorded in advance for real time interaction [http://theinstitute.ieee.…”

Section: Discussionmentioning

confidence: 99%

“…Wearable projector displays image on wearer's body (Rakkolainen et al 2015) 2. Speech recognition system to select the images sources (Trawicki et al 2012;Giannoulis et al 2015;Soda et al 2013;Ishi et al 2015;Turan and Erzin 2016;Toda et al 2012;Rahman et al 2015;Alberth 2013;Mandal et al 2009)…”

Section: Discussionmentioning

confidence: 99%

“…Distributed microphone networks enabling ambient sound capturing without fixed pick-up spots allow speakers to travel within an open space in single or multiple rooms environment. Data fusion of distributed sound signals from different areas can then enhance automatic speech recognition by localisation of speakers and reduction of background noise (Trawicki et al 2012;Giannoulis et al 2015). A microphone array further enhances captured sound quality by putting multiple microphones in grid form to expand the coverage and enable the face orientation estimation of speakers (Soda et al 2013;Ishi et al 2015).…”

Section: Duis For Human Outputs: Body Soundsmentioning

confidence: 99%

See 2 more Smart Citations

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

Hui

Sherratt

2016

J Ambient Intell Human Comput

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The enhancement of human senses electronically is possible when pervasive computers interact unnoticeably with humans in ubiquitous computing. The design of computer user interfaces towards ''disappearing'' forces the interaction with humans using a content rather than a menu driven approach, thus the emerging requirement for huge number of non-technical users interfacing intuitively with billions of computers in the Internet of Things is met. Learning to use particular applications in ubiquitous computing is either too slow or sometimes impossible so the design of user interfaces must be naturally enough to facilitate intuitive human behaviours. Although humans from different racial, cultural and ethnic backgrounds own the same physiological sensory system, the perception to the same stimuli outside the human bodies can be different. A novel taxonomy for disappearing user interfaces (DUIs) to stimulate human senses and to capture human responses is proposed. Furthermore, applications of DUIs are reviewed. DUIs with sensor and data fusion to simulate the sixth sense is explored. Enhancement of human senses through DUIs and context awareness is discussed as the groundwork enabling smarter wearable devices for interfacing with human emotional memories.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Duis For Human Outputs: Body Soundsmentioning

confidence: 99%

See 1 more Smart Citation

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

Hui

Sherratt

2016

J Ambient Intell Human Comput

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A Review of Physical and Perceptual Feature Extraction Techniques for Speech, Music and Environmental Sounds

2016

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Endowing machines with sensing capabilities similar to those of humans is a prevalent quest in engineering and computer science. In the pursuit of making computers sense their surroundings, a huge effort has been conducted to allow machines and computers to acquire, process, analyze and understand their environment in a human-like way. Focusing on the sense of hearing, the ability of computers to sense their acoustic environment as humans do goes by the name of machine hearing. To achieve this ambitious aim, the representation of the audio signal is of paramount importance. In this paper, we present an up-to-date review of the most relevant audio feature extraction techniques developed to analyze the most usual audio signals: speech, music and environmental sounds. Besides revisiting classic approaches for completeness, we include the latest advances in the field based on new domains of analysis together with novel bio-inspired proposals. These approaches are described following a taxonomy that organizes them according to their physical or perceptual basis, being subsequently divided depending on the domain of computation (time, frequency, wavelet, image-based, cepstral, or other domains). The description of the approaches is accompanied with recent examples of their application to machine hearing related problems.

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Multichannel speech recognition using distributed microphone signal fusion strategies

Abstract: Abstract

Cited by 2 publications

References 15 publications

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

A Review of Physical and Perceptual Feature Extraction Techniques for Speech, Music and Environmental Sounds

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