Nokia Technologies Oy

Nokia Corporation

Jari Petteri Sjoberg

Ville Mikael Myllyla

Jukka Vartiainen

Ari Juhani Koski

Anu Huttunen

Jorma Makinen

Riitta Niemisto

Antti Heikki Tapio Sassi

Mari Partio

Tero Takala

Hannu Juhani Pulakka

Emma Jokinen

Paavo Ilmari Alku

Gerald Enzner

Sarmad Malik

An apparatus including at least one processor and at least one memory including computer program code configured to: when the apparatus is in a voice phone call mode of sound capture, output a signal from a first microphone as a primary speech signal, and select one or more second microphones to output a noise reduction signal, where the apparatus comprises at least two of the second microphones, and where selection of the one or more second microphones is based at least partially upon a determined use of the apparatus being either a handportable or an integrated handsfree use; and/or when the apparatus is in a multi-media mode of sound capture select one or more of the microphones to output audio signals based upon both a determined type of sound capture feature being used by the apparatus and based upon a determined orientation of the apparatus.

Audio capture with multiple microphones

An apparatus comprising at least one processor and at least one memory including computer code for one or more programs, the at least one memory and the computer code configured to with the at least one processor to cause the apparatus to at least perform: estimating a signal to noise ratio value for an audio signal; generating a post-filter comprising at least one of: a first formant frequency filter and a second formant frequency filter, wherein the post-filter is dependent on the signal to noise ratio value for the audio signal.

Noise adaptive post filtering

Both a cascade and a multichannel joint Bayesian estimator are provided for suppressing acoustic echo. An expansion basis (Power/Fourier series) is selected to convert a sample-based input signal xinto a DFT-domain multichannel signal [X, . . . X]. The posterior of unknown states (e.g., mean &#x174;and covariance Pof the echo path Wand the mean &#xe2;and covariance Qof the nonlinear coefficients a; or channel-wise mean &#x174;and multichannel covarianceof a compound quantity formed by merging together the echo path Wand the inonlinear coefficient a) and model parameters &#x3b8;are estimated; and Kalman gain factor(s) Kare computed for optimal adaptation of the posterior of unknown states. An echo signal &#x176;is estimated using the multichannel input signal [X, . . . X] and the adapted posterior; and an error signal Eis generated. Residual echo is suppressed by post-filtering the error signal Ewith a weighting function &#x3c8;which depends on the adapted posterior, and the filtered error signal &#x15d;'is then transmitted to a far-end.

Recursive Bayesian controllers for non-linear acoustic echo cancellation and suppression systems

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Kangasala, Finland

Jari Petteri Sjoberg