thankz for the quik and clear reply...at present i am
working on isolated word recognition using
wavelets...i will definetly let u know when i come to
and regarding ANN, i dont have any idea of that
concept...as per ur suggetion i will go through the
concept first and then i will try to use HMM with
can u ask ur friends who have done on wavelets to mail
me the procedure they have followed for speech
recognition...i would like to go in depth of wavelets
to come to a cofirmed conclusion...
--- jitendraajmera <>
> I know a little bit about wavelets....but havent
> tried it for speech recognition. HOwever, some
> colleagues of mine and also other researchers have
> tried it and did not find helpful (for no clear
> However, I am keenly interested in knowing the
> results of your research.....using wavelets.
> Now, about phoneme recognition thingy by
> Paresh....if you have a training database with
> phonetic transcription, ANN is the best choice. At
> the time of recognition/decoding, one has to use
> HMMs....there is no other choice. However, in
> absense of phonetic transcription for the training
> data, using HMMs are inevitable for training too.
> If I am wrong at some point, I would be grateful for
> your corrections.
> best of luck for wavelets,
> --g2 > PS: I think, you forgot to reply your last mail to
> the whole group...so the mails seem to be floating
> between two of us.
> "usha devi"<> wrote:
> If u want to go for phoneme recognition,in my view
> best option would be HMM(hidden markov model)....
> At present i am working on speech recognition(number
> and isolated word recognition) using wavelets...can
> any body suggest me the correct choice of wavelet
> can be used for speech recognition....
> I would like to build up my own filter co-efficients
> for the subband coding...i need suggestions in this
> regard too...
> with regards
> --- jitendraajmera <>
> > Hi Paresh,
> > In MY opinion, these are the answers to your
> > questions:
> > 1. In case of clean speech, MFCC (Mel cepstrum)
> > the most reliable features. However, in noisy
> > conditions, PLP-Rasta are supposed to give better
> > performance.
> > 2. ANN has been widely used for phoneme
> > Ofcourse it is feasible and gives best performance
> > if trained properly. So you should have a good
> > training databse on which you can train your ANN.
> > also depends on what application you are
> > Is it continuous speech recognition? or is it just
> > isolated word recognition?
> > 3. For phonetic transcription...i dont have much
> > idea...however there are some databses distributed
> > by LDC, which are accompanied by the phonetic
> > transcriptions of the word. I think, a visit to
> > website should also help.
> > goodluck,
> > --g2
> > "Paresh Chopdekar"<> wrote:
> > Hi
> > I am a new member of this society. I am a
> > year B.E. student from Mumbai. Formy final year
> > project i have selected Speech Recognition as my
> > topic.
> > I have a few basic questions :-
> > 1 Which is the best method for feature
> > extraction, cepstrum,LPC,PLP,Mel Cepstral
> > 2 I am planning to use a ANN for phoneme
> > recognition, is it feasible & will it provide
> > recognition?
> > 3 How do I construct a word-phoneme database?
> > do i convert a word to its phonetic
> > I am a beginner in this field, so please provide
> > detailed info or liks to sites that provide such
> > info
> > Thanx in advance
> > Paresh C
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