Introduction

Ears have the unique ability to receive and decipher spoken language. Besides that, the ears also have various diverse functions, out of which one function of the ear is the identification of people by their voices (Sharma and Bansal 2013). Forensic auditory analysis has been a subject of methodological and scientific discussion for a long time. It is a globally expanding tendency that the criminals are more willing to disguise their voices to hide their identity, particularly in cases of extortion, threatening calls, emergency calls to the police (Zhang and Tan, 2007). Every individual in this world has a unique voice. The voice of no two individuals is the same due to physiological dissimilarities. The individuality of the individual’s voice can be employed to verify the person’s identity. Every speaker has unique features of speaking besides those physiological dissimilarities such as the use of specific accent, intonation style, rhythm, suffering from any disorder that affects the speaking ability and causes tremors, etc. (Zheng and Li., 2017). There are many possibilities available to the speaker to manipulate his/her voice to falsify an automatic recognition system or even the human ear (Perrot, Aversano, and Chollet, 2007). Biometric access control systems, Automatic Speaker Recognition Systems, auditory analysis in forensics, etc. are several examples of speaker and voice recognition (Lal and Nath N. J., 2015). Biometric accessed security systems are built based on the unique features of humans like voice, fingerprints, etc. These types of systems provide an additional barrier to stop the unauthorized approach for the protection of data by detecting the user’s particular behavioral or physiological features. Biometric accessed security systems are more authentic than the standard traditional method. There are higher demands on speaker identification on modeling the vocal tract features of speakers such as an illness, to provide a more secure approach to financial or sensitive information. The verification of speakers gives more barriers to stop uncertified access to secure the data and also improves the protection provided by personal identification (Li, Yang, and Dai, 2014).

Apprehensive voice is mainly that voice which reflects fear, anger, anxiety, nervousness, shivered voice because of illness which in final disguises the voice intentionally or unintentionally. An apprehensive speech is that disguised speech of the speaker which is recorded under the influence of any threat, fear, anger, and nervousness, etc. It also comes under the disguised voice category. This type of voice is used for various criminal and illicit purposes such as fraud or spam calls, threatening calls, and also during the sample collection process of suspects. In the forensic science field, finding a solution to differentiate between apprehensive voices from normal voices will give better indications to the investigator during the investigation process. Voice disguise is an intentional act of a speaker to alter, distort, deviate, or manipulate their normal voice to hide or falsify their identity (Klevans & Rodman, 1998). In the field of acoustic analysis as well as in forensic science, the speaker recognition process or techniques are inexorable and they are used in the speaker identification. Speaker recognition based on Voiceprints is defined as the recognition of an individual or speaker’s identity by using their voiceprints. Various researches proposed that the voiceprint of an individual has a distinct quality of uniqueness, durability, and strength, which always remain stable and become unchanged in adulthood except for some disorders. It is also suggested that the voice of no individuals is the same due to physiological dissimilarities. Every speaker has unique features of speaking besides those physiological dissimilarities such as the use of specific accent, intonation style, rhythm, suffering from any disorder that affects the speaking ability, and causes tremors, etc. Intonation patterns of voice are the patterns of variation generated by the rise and fall in the pitch of the voice. These intonation patterns are also helpful in speaker recognition in case of a disguised or apprehensive voice.