Voice based self help System: User Experience Vs Accuracy

TL;DR

This paper explores how integrating speech recognition with dedicated language processing can enhance user experience in voice-based self-help systems, emphasizing the balance between accuracy and usability.

Contribution

It proposes combining speech recognition with separate language processing to improve system performance and user experience in voice-based self-help applications.

Findings

Enhanced accuracy through combined processing

Improved user satisfaction with integrated systems

Framework for combining speech and language engines

Abstract

In general, self help systems are being increasingly deployed by service based industries because they are capable of delivering better customer service and increasingly the switch is to voice based self help systems because they provide a natural interface for a human to interact with a machine. A speech based self help system ideally needs a speech recognition engine to convert spoken speech to text and in addition a language processing engine to take care of any misrecognitions by the speech recognition engine. Any off-the-shelf speech recognition engine is generally a combination of acoustic processing and speech grammar. While this is the norm, we believe that ideally a speech recognition application should have in addition to a speech recognition engine a separate language processing engine to give the system better performance. In this paper, we discuss ways in which the speech recognition engine and the language processing engine can be combined to give a better user experience.