Multiple feed forward ANNs of different architectures have been developed and their achievements reported. r-Distype program automatically develops a feed forward ANN that tests the spoken word (which includes /r/ phoneme) to detect any possible type of distortion.
RECOGNIZE R PRAAT SOFTWARE
In this paper we take the Arabic /r/ phoneme distortion that is somewhat common among native speakers as a case study.To do this, r-Distype program is developed as a script written using Praat speech processing software tool. I'm not sure if I can predict how much time and effort would be required to get 70% accuracy, since it would depend on the nature of your task my sense is that 90%+ would definitely be very hard.The paper is not for recognizing normal formed speech but for distorted speech via examining the ability of feed forward Artificial Neural Networks (ANN) to recognize speech flaws. with many speakers, microphones, or recording environments), there are plenty of things that you can do. You could use something like sox to determine the frequency spectrum (using something called the fast Fourier transform) of an utterance and classify speech as "male" or "female" depending on some summary statistic like the average frequency (see ). Basically, male and female voices differ in their fundamental frequency - according to Wikipedia ( ), male voices are between 85-180Hz, while female voices are 165Hz-255Hz. Lastly, you could try to implement a very crude gender-recognition algorithm without getting into the speech recognizer itself, if you know a little bit of signal processing. A search of Google Scholar reveals many people who've written Master's or PhD theses using Sphinx, so that could be a good place to start.
RECOGNIZE R PRAAT CODE
Some academic researchers post their code online, and/or might be willing to share it with you. emotion recognition: predicting the speaker's emotion from a speech utterance (a very new area of research).Īccording to, CMU Sphinx, which is probably the leading open-source speech recognizer out there, does not support speaker identification ( ) I'm doubtful that it has any of the other capabilities described above.speaker diarization: taking an audio file with multiple files and labeling which segments of speech belong to which speaker.speaker verification: accepting or rejecting an utterance as belonging to a speaker (imagine a "voiceprint"-type authorization system).speaker identification: predicting, from a set of possible speakers, the most likely speaker in a speech utterance.age identification: predicting the age of the speaker.gender identification (sometimes called gender recognition): predicting the gender of the speaker from the speech utterance.If you have some background in implementing signal-processing or machine-learning algorithms, you could try looking up academic papers using some of these search terms: These are open research problems, and, unfortunately, I'm not aware of open-source packages that can do these things out of the box.
I'm a graduate student doing speech recognition research.