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theBoom Quiet reviewed on TreoCentral

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UmeSkype Screencast

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New release of UmeSkype!

I am excited to announce the availability of UmeSkype v 1.0.1.0 . It has a "listening" indicator which shows whether UmeSkype is listening to you (green), or not (red). You can also toggle the listening mode using the ESC key. It will also toggle the mode automatically to not listening when you are on a call.

theBoom and theBoom O reviewed on Treocentral

A detailed review of theBoom noise cancelling headsets by a Treo user.

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Skype Journal: Importance of clear audio for VoIP

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Skype Journal: SkypeOut now Free in North America

Skype's announcement today would be a welcome change for many Skype users, and the impetus for many to start using Skype.

One annoyance that people (in N. America at least) might have is that you have to type in 12 characters every time you want to dial a number (e.g. +18882303300). UmeSkype allows you to dial numbers (US/Canada) using your voice, so you just say "dial eight eight eight two three zero three three zero zero", which is way faster than clicking on the little window in Skype and typing in 12 characters. We hope that this will make UmeSkype a valuable tool for users. Some obvious enhancements such as "push-to-talk" or "push-to-activate" are in the works.

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More on Speech Audio quality for Speech Recognition

Audio quality is a critical factor in Speech Recognition performance. How do we define audio quality? Or to put it another way, what do we mean when we say that good quality audio is being received by the speech recognition software (or, for that matter, by the listener at the other end of an audio communications channel)?

One of the indicators of "good" audio is how closely it resembles the input audio that was intended to be transmitted. In case of speech recognition and telephone/VoIP communication, this input audio is the set of utterances spoken by the user(s) into the microphone. In more technical terms of the audio system, this can be described as having a "flat frequency response". It implies that the components of the audio signal at all the frequencies are preserved intact in the output. Speech recognition software relies on the spectrum of the audio signal to determine "what" was spoken, so the more closely the audio signal's frequency components resemble those of the user's spoken audio, the more accurate the recognition will be.