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Microphone

About: Microphone is a(n) research topic. Over the lifetime, 39999 publication(s) have been published within this topic receiving 337352 citation(s). The topic is also known as: mic & mike.


Papers
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01 Jan 2001
TL;DR: This paper presents a meta-modelling architecture for microphone Array Processing that automates the very labor-intensive and therefore time-heavy and expensive process of manually shaping Microphone Arrays for Speech Input in Automobiles.
Abstract: I. Speech Enhancement.- 1 Constant Directivity Beamforming.- 2 Superdirective Microphone Arrays.- 3 Post-Filtering Techniques.- 4 Spatial Coherence Functions for Differential Microphones in Isotropic Noise Fields.- 5 Robust Adaptive Beamforming.- 6 GSVD-Based Optimal Filtering for Multi-Microphone Speech Enhancement.- 7 Explicit Speech Modeling for Microphone Array Speech Acquisition.- II. Source Localization.- 8 Robust Localization in Reverberant Rooms.- 9 Multi-Source Localization Strategies.- 10 Joint Audio-Video Signal Processing for Object Localization and Tracking.- III. Applications.- 11 Microphone-Array Hearing Aids.- 12 Small Microphone Arrays with Postfilters for Noise and Acoustic Echo Reduction.- 13 Acoustic Echo Cancellation for Beamforming Microphone Arrays.- 14 Optimal and Adaptive Microphone Arrays for Speech Input in Automobiles.- 15 Speech Recognition with Microphone Arrays.- 16 Blind Separation of Acoustic Signals.- IV. Open Problems and Future Directions.- 17 Future Directions for Microphone Arrays.- 18 Future Directions in Microphone Array Processing.

1,265 citations

Proceedings ArticleDOI
07 May 1996
TL;DR: A new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations and demonstrates that the subjective and objective results are much better than existing methods.
Abstract: This paper addresses the problem of single microphone frequency domain speech enhancement in noisy environments. The main characteristics of available frequency domain noise reduction algorithms are presented. We have confirmed that the a priori SNR estimation leads to the best subjective results. According to these conclusions, a new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations. The obtained solutions demonstrate that the subjective and objective results are much better than existing methods.

712 citations

Proceedings ArticleDOI
Hong Lu1, Wei Pan1, Nicholas D. Lane1, Tanzeem Choudhury1, Andrew T. Campbell1 
22 Jun 2009
TL;DR: This paper proposes SoundSense, a scalable framework for modeling sound events on mobile phones that represents the first general purpose sound sensing system specifically designed to work on resource limited phones and demonstrates that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.
Abstract: Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sensing applications. Perhaps the most ubiquitous and unexploited sensor on mobile phones is the microphone - a powerful sensor that is capable of making sophisticated inferences about human activity, location, and social events from sound. In this paper, we exploit this untapped sensor not in the context of human communications but as an enabler of new sensing applications. We propose SoundSense, a scalable framework for modeling sound events on mobile phones. SoundSense is implemented on the Apple iPhone and represents the first general purpose sound sensing system specifically designed to work on resource limited phones. The architecture and algorithms are designed for scalability and Soundsense uses a combination of supervised and unsupervised learning techniques to classify both general sound types (e.g., music, voice) and discover novel sound events specific to individual users. The system runs solely on the mobile phone with no back-end interactions. Through implementation and evaluation of two proof of concept people-centric sensing applications, we demostrate that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.

666 citations

Proceedings Article
01 Jan 2003
TL;DR: The algorithm is noise and distortion resistant, computationally efficient, and massively scalable, capable of quickly identifying a short segment of music captured through a cellphone microphone in the presence of foreground voices and other dominant noise, out of a database of over a million tracks.
Abstract: We have developed and commercially deployed a flexible audio search engine. The algorithm is noise and distortion resistant, computationally efficient, and massively scalable, capable of quickly identifying a short segment of music captured through a cellphone microphone in the presence of foreground voices and other dominant noise, and through voice codec compression, out of a database of over a million tracks. The algorithm uses a combinatorially hashed time-frequency constellation analysis of the audio, yielding unusual properties such as transparency, in which multiple tracks mixed together may each be identified. Furthermore, for applications such as radio monitoring, search times on the order of a few milliseconds per query are attained, even on a massive music database.

648 citations

Journal ArticleDOI
Abstract: 1. Sound transmission was measured in open fields, mixed decidous forest with and without leaves and coniferous forest in Dutchess County, New York. Attenuation of white noise and pure tones was measured between one microphone close to a loudspeaker and another microphone 100 m away, at the same height. Graphs of excess attenuation (E.A. in dB/100 m) against frequency were obtained at 0.15, 1, 2, 5, and 10 m above the ground. An analysis of variance was conducted to estimate effects of height, frequency and habitat. 2. Height and frequency affect sound transmission more than habitat. With a sound source close to the ground (15 cm and 1 m) all frequencies were more attenuated than at greater heights. The patterns of E.A. as a function of sound frequency were basically similar in all habitats. At all source heights the lower the frequency the better the sound carried, with the exception that close to the ground, sounds below 2 kHz were excessively attenuated. Comparing open field and forest, trees improved transmission of frequencies below 3 kHz, especially close to the ground. 3. Some general trends can be predicted for maximization of transmission distances of animal sounds in these habitats. For an animal vocalizing higher than 1 m above the ground, the lower the frequency the further the sound travels. Close to the ground, low frequencies are again preferred for maximization of transmission distances, but the frequencies must be pitched above a range of attenuated, low-pitched sounds, the limits of which vary to some extent with habitat, creating the ‘sound window’ of Morton. This ‘window’ of least-attenuated frequencies, only occurring close to the ground, tends to be pitched somewhat lower in forest than in open habitats. However, for an animal producing sounds in the habitats tested, perch height and sound frequency are more important than the habitat in determining how far the sound will carry.

611 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20224
2021660
20201,637
20191,955
20182,056
20171,884