Tài liệu Digital Signal Processing Handbook P48 docx

Furui, S. & Rosenberg, A.E. “Speaker Verification”

Digital Signal Processing Handbook

Ed. Vijay K. Madisetti and Douglas B. Williams

Boca Raton: CRC Press LLC, 1999

c 1999 by CRC Press LLC

48

Speaker Verification

Sadaoki Furui

Tokyo Institute

of Technology

Aaron E. Rosenberg

AT&T Labs — Research

48.1 Introduction

48.2 Personal Identity Characteristics

48.3 Vocal Personal Identity Characteristics

48.4 Basic Elements of a Speaker Recognition System

48.5 Extracting Speaker Information from the Speech Signal

48.6 Feature Similarity Measurements

48.7 Units of Speech for Representing Speakers

48.8 Input Modes

Text-Dependent (Fixed Passwords) • Text Independent (No

Specified Passwords) • Text Dependent (Randomly Prompted

Passwords)

48.9 Representations

Representations That Preserve Temporal Characteristics •

Representations That do not Preserve Temporal Character￾istics

48.10 Optimizing Criteria for Model Construction

48.11 Model Training and Updating

48.12 Signal Feature and Score Normalization Techniques

Signal Feature Normalization • Likelihood and Normalized

Scores • Cohort or Speaker Background Models

48.13 Decision Process

Specifying Decision Thresholds and Measuring Performance

• ROC Curves • Adaptive Thresholds • Sequential Decisions

(Multi-Attempt Trials)

48.14 Outstanding Issues

Defining Terms

References

48.1 Introduction

Speaker recognition is the process of automatically extracting personal identity information by anal￾ysis of spoken utterances. In this section, speaker recognition is taken to be a general process whereas

speaker identification and speaker verification refer to specific tasks or decision modes associated with

this process. Speaker identification refers to the task of determining who is speaking and speaker

verification is the task of validating a speaker’s claimed identity.

Many applications have been considered for automatic speaker recognition. These include secure

access control by voice, customizing services or information to individuals by voice, indexing or

labeling speakers in recorded conversations or dialogues, surveillance, and criminal and forensic in￾vestigations involving recorded voice samples. Currently, the most frequently mentioned application

c 1999 by CRC Press LLC