Hi all,

I'm very new with both DSP and Speech recognition. So could you please
let me know:

+ What type of filters used to remove noise since my input is taken in a
noisy environment.
+ Some documents that discuss the frequency range of human voice?
+ Other types of filters?
+ Algorithms/techniques/models used to retrieve and match
sample/pattern.

These are all I think I need to work with speech recognition. If I miss
anything, please let me know.

I really appreciate if you guys can give me a hand to start studying
this field.

Thanks in advance,
Pete.

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Hey man!

To answer a few of your queries:
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1) Noise Cancellation is a very hot research field and there are numerous
methods to do so. I will suggest a few noise cancellation methods in the
ascending order of difficulty - spectral subtraction (multiband inclusive),
frequency scaling methods, kalman filtering, global soft decision method, signal
subspace methods and auditory scene analysis / blind source separation. For just
a start you would want to work on spectral subtraction.

References:
Multiband spectral subtraction for speech enhancement [Sunil Devdas Kamant, MS
Thesis]

speech enhancement for personal communications using an adaptive gain equalizer.
Neils Westerlund, Mattias Dahl and Ingvar Claesson
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2) Regarding the frequency range of human utterance, take it from me that it
wont exceed 4kHz, so 8kHz sampling is just fine.
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3) Other types of filters for noise cancellation: well, wavelets. but most
filterbanks are used to split the signal into sub-bands.
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4) Pattern Matching: just go through the chapter on HMMs from rabiner, or the
famous tutorial for that matter... You just need to know how to fit a cluster of
points in space into gaussians. That should give you a good start for speech
recognition.
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