Synthetic Voice Harmonization: A Fast and Precise Method

Abstract

Musicians often lack the ability to harmonize their voices within a track. To help with this matter, a tool can be developed for detecting the scale or key in which a track is sung and synthesizing pitches to make a triadchord or a tetrachord (combinations of three or four notes that fit in the scale's harmony) for each corresponding tone in the melody. In this paper, we present a fast and precise method to detect the pitch of voice and shift it to the appropriate frequencies, consequently building up a harmony out of the original melody. Four techniques are involved in this sequential process: segmentation into consonant and vowel intervals, pitch detection by the McLeod Pitch Method (MPM), functional harmony for establishing a cadence, and pitch shifting by means of a phase vocoder.

Speech Segmentation Using Dynamic Windows and Thresholds for Arabic and English Languages

“…In the information society, speech is used not only in its original form but also through many digital electronic devices (Zhang and Kuo, 2001) mobile phones grow rapidly, wired telephone systems become digital and Internet phones and audio are common in use. On the other hand, computers may also speak to humans by synthetic voice (Juan et al, 2015) and listen to us using speech recognition. To understand these processes for both human and machine, we have to study carefully the structures and functions of spoken language: how to produce and perceive it and how speech technology may help us to communicate (Hennig and Chellali, 2012) Speech segmentation is the process of splitting the speech into separately words and each word is saved in separated audio file for the upcoming processing as shown in Fig.…”