DSP Application

In this experiment, we had to perform an application on DSP processor. OT was a group experiment. The members were Chetan Jogi, Mohit Karandikar, Ameya Lokre, and Dhvanil Mandalia. Signal processing of a 1D signal was to be done. We chose the topic 'Audio feature extraction'. 

I reviewed the patent Audio processing techniques for semantic audio recognition.

Patent no.: US20140180673 A1

Summary:

A system or method was defined for determining the semantic info from audio. the incoming audio signl is sampled and processed to extract features like temporal, harmonic and rhytmic features. The extratced featurs are compared to stored reference signals. Features that are most similar to one or more templates from comparison are identified according to the tags. These tags are used to determine semantic audio data that includes genre, instrumentation, style, acoustical, dynamics and emotive description descriptor.

The paper I reviewed was Audio feature extraction for classification using relative transformation.

Summary:

Audio features that have been successfully used for audio classification include mel-frequency cepstral coefficeints (MFCCs), spectral similarity, timbral texture. Among these, MFCCs are widely used. Relative transformation has been applied to deal with sparse, noisy, imbalance problems, as it is learns the abilities from human beings. For each audio, a set of feature vectors can be constructed by computing MFCCs. One way of generating a single vector feature for the audio is to simply randomly subsmaple the overall distribution of these vectors. Here a new approach called Relative Transformation Vector Quantization (RTQV) is proposed.

We implemented a system which stores time domian reference signal and correlates it with a test signal. If the correlation output is 1 then the signal is identified.

https://drive.google.com/drive/folders/0BwvLoQVdPTK3SEJjVUxvbEd0bTg