Vocal Isolating and Amplifying Headphones

The goal of this project is to create headphones that isolate the vocals in a media stream and amplify them

Background
The goal of this project is to create a device that assists the hard of hearing in picking out and distinguishing human vocals, in media like television and film, from background noise and other sounds that can distract from overall speech intelligibility. This is being explored from several different approaches, first is a simple filter that lowers the perceived volume of non-human speech frequencies while leaving the spectrum that the human voice commonly falls in (1-4kHz) untouched. This method has the drawback of not attenuating noises that are non-human in origin but occupy the same frequency range. The second approach is to utilize a blind source separation algorithm (BSS) to analyse and separate the individual components that make up the mixed audio signal. This will allow us to extract the human speech from the signal and amplify it separately from the source signal before remixing at the output of the device. The drawback to this method is the processing time required to perform the BSS, which could delay the audio signal by enough for the offset from the video signal to be noticeable.

Specifications
Required:

Client Request: Client would like a vocal audio to become clearer to listen to Specification: Vocal audio range to be variably increased from +0db to +10db

Client Request: Client would like a reduction in background noise and nonspeech Specification: An reduction in nonspeech noise by variable -0db to -10db

Optional:

Client Request: Client would like the device to be wireless from the audio source Specification: Design must only have wires at the device for headphones and power.

Client Request: Client would like the device to support multiple users Specification: Allow for full range of options to multiple hearing outputs

Client Request: Client would like the device to have learning capabilities Specification: Create a learning system to tune user specific Equalization values.

Equalizer chip: LMC835
The LMC835 is a 12 band, digitally controlled equalizer. It is capable of boosting or cutting by 6 or 12 decibels and can be reprogrammed on the fly. This chip or something similar, coupled with a micro controller will help in giving the vocal speech range the required boosting.

Amplifier: Objective 2
The Objective 2 is an open source HiFi headphone amplifier with dual gain stage and plenty of room for growth and modifications. With schematics readily available, iterating off of this design can help our project move forward and maintain reasonable package size.

Microcontroller: Digilent WiFire
The WiFire micro controller is a smaller microcontroller that has a DSP enhanced core contained inside of it. This will give us the proper processing hardware in order to create voice separation without introducing latency.

Blind Source Separation
This is an unsolved problem in signal processing, but there are various algorithms that give good approximations for separating various types of mixed signals. Several notable algorithms include: Independent Component Analysis (ICA), Non-negative Matrix Factorization (NMF), and Principal Component Analysis (PCA).

Voice Recognition
Voice recognition algorithms are another avenue for determining what is (and isn’t) speech in a signal and include using Hidden Markov Models (HMM) and neural networks for unsupervised learning.