[SOLVED] CS6300 – Mini Project 2 -Speech Technology

You need to do the following task​:

1. Isolated Digit Recognition using Discrete HMMs (​code). Use the given features also​ extract your own features and compare the results.
2. Use the HMMs trained in task 1 to recognize continuous digits. You need to concatenate the HMMs trained in task 1 to recognize continuous digits. Use only the given features.

Datasets​:

Digit dataset:  This dataset consists of spoken utterances.  The MFCC feature files and the original .wav files given.

Data: ​download here​, Group Mapping: ​Download here

Continues digits dataset:

• Download development data from ​here ​and test data from ​here.​
• The data contains directories with the group numbers.
• Each directory contains MFCC features from utterances of multiple digits

(corresponding to the isolated digits assigned to your batch).

• The set of digits uttered are given below: symbol – uttered word 1 – one 2 – two 3 – three 4 – four 5 – five 6 – six 7 – seven 8 – eight 9 – nine z – zero o – o
• In development data, the file name represents spoken digits. Eg. In file 534.mfcc, the digits spoken are five three four.
• Test data consists of 5 unlabeled sequences (blind data). Provide the possible sequence of digits obtained in the report.

Feature File Format​:

• The data given are the MFCC features of speech audio.
• Structure of MFCC file: The first line of the MFCC file contains two space-separated integers. First integer N​C​ – The dimension of the feature vector (The number of MFC coefficients) Second integer N​F​ – The number of frames, the .wav file is divided into.
• The next NF rows contain the MFCC features of dimension NC. Each row corresponds to a feature vector in the sequence.  Please note that NF varies with the example.

Guidelines​:

1. You need to plot ROC, DET and confusion matrices for task 1.
2. You can include graphs and tables for your results.