[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 NC The dimension of the feature vector (The number of MFC coefficients) Second integer NF 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.