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SPEECH PROCESSING

By-
1.Hawal Suyog R.
2.Hajare Vinayak B.
3.Sakhawalkar Rohit R.
4.Akhil Bhan

Under Guidance of
Mr. M. M. Kamble

Introduction

Prior Definitions

Pitch : Defined as the perceptual appreciation of
the highness or the lowness of a sound
It is related to the periodicity of a sound.

Frequency : Physical attribute of a sound or any type other of signal. Describes the amount of times that a repeated event occur per unit of time.

Fundamental Frequency : In a complex sound or
signal, it is the lowest partial.

Application of Pitch Tracking Score Following



Musical Queries by singing or humming

Acoustic feature for Human-Computer Interaction

Sound-Editing Program like pitch-shifting and time-scaling operation
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CONTINUOUS SPEECH PROCESSING
INTRODUCTION

 Continuous Speech Processing (CSP) is a feature available with select boards supporting high-performance, speech enabled applications.
 This technology enhances existing speech technologies by providing board-level firmware that processes real time voice signals to identify human speech input and present it to the host platform for speech recognition.
 The real-time functions include both echo cancellation and Voice Activity Detection (VAD).
FEATURES AND BENEFITS
CSP has the following features and offers these benefits:
 Provides low implementation cost and enhanced System performance
 Reduces system latency, increases recognition accuracy, and improves overall system response time
 Scalable
 Flexible
APPLICATIONS
CSP can be employed in applications such as:
 Voice portals which includes: weather, traffic, movies, restaurant guides, etc.
 Speech enabled Interactive Voice Response (IVR)
 Speech activated dialing
 Developers can develop and deploy enhanced speech technology platforms that are enabled for voice commands with first-rate accuracy and performance.
CONTINUOUS SPEECH PROCESSING
 Speech technologies can benefit from CSP because it provides board-level firmware that processes real-time voice signals to identify human speech input and present it to the host platform for speech recognition.
 The software consists of a library of functions, device drivers, firmware, sample demonstration programs, and technical documentation to help create Automated Speech Recognition (ASR) applications.
SPEECH TECHNOLOGIES
Speech recognition provides host-based recognition engines and a variety of tools for developing and implementing robust applications.
There are two different approaches:
1. Traditional Speech Processing
2. Competitive Speech Processing Feature
 TRADITIONAL SPEECH PROCESSING
 COMPETITIVE SPEECH PROCESSING
 HOW CONTINUOUS SPEECH PROCESSING WORKS
Tap length:
The duration of an echo is measured in tens of milliseconds (ms). The number of milliseconds an echo canceller removes is known as the length of the echo canceller.
Adaptation Modes
The echo canceller has two adaptation modes:
1. Fast mode for rapid convergence
2. Slow mode for slower convergence
2. VOICE ACTIVITY DETECTOR:
VAD is the CSP component that examines the incoming signal and determines if the signal contains significant energy to be identified as speech.
VAD detects audio energy and triggers data transmission only when speech is present.
VAD technology in CSP includes a pre-speech buffer that produces better voice recognition using less host processing and enhances the accuracy of speech detection.
Barge-in:
CSP supports various application-friendly features, such as the ability to interrupt speech prompts by speaking over them known as “barge-in”.
The combination of echo cancellation and VAD can be used to effect barge-in.
The barge-in feature stops the playing of the prompt upon detection of audio energy exceeding the threshold.
HARDWARE SYSTEM REQUIREMENTS
For boards with Continuous Speech Processing:
Single or dual processor PCI or PCI Express bus, or • Compact PCI bus computer
Operating system hardware requirements vary according • to the number of channels being used
CONCLUSION
 CSP now includes a silence compressed streaming feature, which removes the silence between the caller’s utterances before streaming to the host.
 This saves host processing cycles and allows for increased port density. The amount of silence compression and energy thresholds are configurable.
Hi I'm new to speech processing and in need of matlab code for babble noise removal. Will anyone please help me in that area