Harmonic convergence coordinates swarm mating by enhancing mate detection in the malaria mosquito Anopheles gambiae

The mosquito Anopheles gambiae is a major African malaria vector, transmitting parasites responsible for significant mortality and disease burden. Although flight acoustics are essential to mosquito mating and present promising alternatives to insecticide-based vector control strategies, there is limited data on mosquito flight tones during swarming. Here, for the first time, we present detailed analyses of free-flying male and female An. gambiae flight tones and their harmonization (harmonic convergence) over a complete swarm sequence. Audio analysis of single-sex swarms showed synchronized elevation of male and female flight tones during swarming. Analysis of mixed-sex swarms revealed additional 50 Hz increases in male and female flight tones due to mating activity. Furthermore, harmonic differences between male and female swarm tones in mixed-sex swarms and in single-sex male swarms with artificial female swarm audio playback indicate that frequency differences of approximately 50 Hz or less at the male second and female third harmonics (M2:F3) are maintained both before and during mating interactions. This harmonization likely coordinates male scramble competition by maintaining ideal acoustic recognition within mating pairs while acoustically masking phonotactic responses of nearby swarming males to mating females. These findings advance our knowledge of mosquito swarm acoustics and provide vital information for reproductive control strategies.

Forensic Aspects of Voice Analysis in India

The area of forensic speech and audio analysis encompasses a vast range of operations, the much more prominent of which is, without the need of a doubt, speaker identification. In addition, comprehensibility improvement of the recorded voice signal, analysis of disputed speech, and assessment of the legitimacy of audio recordings are also activities in the field. Using voice analysis, the examiner has two ideas about how to make an identification. Initially, he or she might compare the accent, conversational habits, breathing rhythms, and intonations of the evidence sample with the suspicious samples. After then, the corresponding voiceprints are compared. Voice parametrization is the process of converting a voice signal into a set of selected features that emphasize the speaker unique characteristics. The goal of this modification is to establish a new depiction that is more concise and more appropriate to speaker characterization. While evaluating deteriorated acoustic situations, recognizing voice parts becomes challenging. Time interval measure, zero-crossing rate, pitched spectrum analysis, higher cognitive statistics in the LPC residual domain, and fusions of various characteristics are among the Voice Activity Detection (VAD) approaches employed. Keywords: Voice, analysis, crime, Forensic, India.

Research on a voice changed by distortion

The concept and essence of distortion are considered from a technical stand-point and criminal law perspective. The most common ways of distorting a voice and a speech are provided, as well as certain methods of detecting an intentional change in a voice and human speech by computer tools and linguistic analysis. Some software and hardware tools changing a speech signal both in real time and in a pre-prepared recording are analyzed. To solve diagnostic and identification tasks, a pressing issue in forensic video and audio analysis is studied which is addressed to forensic experts in this field more often.

A Dynamic Model of Speech for the Social Sciences

Speech and dialogue are the heart of politics: nearly every political institution in the world involves verbal communication. Yet vast literatures on political communication focus almost exclusively on what words were spoken, entirely ignoring how they were delivered—auditory cues that convey emotion, signal positions, and establish reputation. We develop a model that opens this information to principled statistical inquiry: the model of audio and speech structure (MASS). Our approach models political speech as a stochastic process shaped by fixed and time-varying covariates, including the history of the conversation itself. In an application to Supreme Court oral arguments, we demonstrate how vocal tone signals crucial information—skepticism of legal arguments—that is indecipherable to text models. Results show that justices do not use questioning to strategically manipulate their peers but rather engage sincerely with the presented arguments. Our easy-to-use R package, communication, implements the model and many more tools for audio analysis.