Microphone

About: Microphone is a research topic. Over the lifetime, 39999 publications have been published within this topic receiving 337352 citations. The topic is also known as: mic & mike.

Microphone mounting structure for a sound amplifying respirator and/or bubble suit

Abstract: A microphone mounting structure for mounting a microphone to a respiratory mask and/or bubble suit through a hole therein. The microphone mounting structure is thus able to convert a conventional respiratory mask and/or bubble suit into a sound amplifying mask and/or bubble suit. The microphone mounting structure comprises a tubular plug and a tubular locking mechanism. The tubular plug has a closed end, an open end and a central portion disposed therebetween. The closed end of the tubular plug has a larger outer diameter than an outer diameter of the central portion. The open end has a plurality of resilient fingers defined by slots in the open end, the resilient fingers having finger tips which project radially outwardly with respect to the tubular plug. The microphone is dimensioned so as to fit coaxially inside the is tubular plug, and preferably, a grommet is provided around the microphone. The tubular locking mechanism has an inner diameter substantially equal to the outer diameter of the central portion and a longitudinal length slightly shorter than a combination of the central portion and the open end. Accordingly, the tubular locking mechanism is slidable over the resilient fingers after the tubular plug is inserted through the hole in the mask. This forces the resilient fingers radially inwardly until the entire tubular locking mechanism has passed over the finger tips of the resilient fingers at which time the finger tips snap outwardly to thereby lock the microphone mounting structure to the respiratory mask/bubble suit. Amplification circuitry is also provided.

Acoustic Beamforming for Speaker Diarization of Meetings

Abstract: When performing speaker diarization on recordings from meetings, multiple microphones of different qualities are usually available and distributed around the meeting room. Although several approaches have been proposed in recent years to take advantage of multiple microphones, they are either too computationally expensive and not easily scalable or they cannot outperform the simpler case of using the best single microphone. In this paper, the use of classic acoustic beamforming techniques is proposed together with several novel algorithms to create a complete frontend for speaker diarization in the meeting room domain. New techniques we are presenting include blind reference-channel selection, two-step time delay of arrival (TDOA) Viterbi postprocessing, and a dynamic output signal weighting algorithm, together with using such TDOA values in the diarization to complement the acoustic information. Tests on speaker diarization show a 25% relative improvement on the test set compared to using a single most centrally located microphone. Additional experimental results show improvements using these techniques in a speech recognition task.

Noise Reduction in Speech Processing

Abstract: Noise is everywhere and in most applications that are related to audio and speech, such as human-machine interfaces, hands-free communications, voice over IP (VoIP), hearing aids, teleconferencing/telepresence/telecollaboration systems, and so many others, the signal of interest (usually speech) that is picked up by a microphone is generally contaminated by noise. As a result, the microphone signal has to be cleaned up with digital signal processing tools before it is stored, analyzed, transmitted, or played out. This cleaning process is often called noise reduction and this topic has attracted a considerable amount of research and engineering attention for several decades. One of the objectives of this book is to present in a common framework an overview of the state of the art of noise reduction algorithms in the single-channel (one microphone) case. The focus is on the most useful approaches, i.e., filtering techniques (in different domains) and spectral enhancement methods. The other objective of Noise Reduction in Speech Processing is to derive all these well-known techniques in a rigorous way and prove many fundamental and intuitive results often taken for granted. This book is especially written for graduate students and research engineers who work on noise reduction for speech and audio applications and want to understand the subtle mechanisms behind each approach. Many new and interesting concepts are presented in this text that we hope the readers will find useful and inspiring.

A robust adaptive beamformer for microphone arrays with a blocking matrix using constrained adaptive filters

Abstract: This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a new adaptive blocking matrix using coefficient-constrained adaptive filters (CCAFs) and a multiple-input canceller with norm-constrained adaptive filters (NCAFs). The CCAFs minimize leakage of the target-signal into the interference path of the GSC. Each coefficient of the CCAFs is constrained to avoid mistracking. The input signal to all the CCAFs is the output of a fixed beamformer. In the multiple-input canceller, the NCAFs prevent undesirable target-signal cancellation when the target-signal minimization at the blocking matrix is incomplete. The proposed beamformer is shown to be robust to target-direction errors as large as 200 with almost no degradation in interference-reduction performance, and it can be implemented with several microphones. The maximum allowable target-direction error can be specified by the user. Simulated anechoic experiments demonstrate that the proposed beamformer cancels interference by over 30 dB. Simulation with real acoustic data captured in a room with 0.3-s reverberation time shows that the noise is suppressed by 19 dB. In subjective evaluation, the proposed beamformer obtains 3.8 on a five-point mean opinion score scale, which is 1.0 point higher than the conventional robust beamformer.

Spatial Sound Reproduction with Directional Audio Coding

Abstract: Directional audio coding (DirAC) is a method for spatial sound representation, applicable for different sound reproduction systems In the analysis part the diffuseness and direction of arrival of sound are estimated in a single location depending on time and frequency In the synthesis part microphone signals are first divided into nondiffuse and diffuse parts, and are then reproduced using different strategies DirAC is developed from an existing technology for impulse response reproduction, spatial impulse response rendering (SIRR), and implementations of DirAC for different applications are described