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Source Transformation01:15

Source Transformation

Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that when...
Source Transformation for AC Circuits01:11

Source Transformation for AC Circuits

The process of source transformation in the frequency domain entails the conversion of a voltage source, positioned in series with an impedance, into a current source that is parallel to an impedance, or the other way around. It is essential to maintain the following relationships while transitioning from one source type to another.
Transcription01:17

Transcription

Transcription is the synthesis of RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in correctly synthesizing messenger RNA (mRNA). Transcriptional regulation is responsible for the differentiation of different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds of RNA Molecules
In eukaryotes,...
Transcription01:10

Transcription

Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...
Air-entraining Agents01:27

Air-entraining Agents

Air-entraining agents improve the durability and workability of concrete in climates with frequent freezing and thawing. These agents prevent cracks by introducing small air bubbles into the mix, creating spaces accommodating water expansion when temperatures drop. The air-entraining agents lower the surface tension of water, forming stable, small air bubbles. This method is more effective than having accidental large voids, as the intentional, smaller, and evenly distributed air voids improve...
Impression Management Techniques IV: Altercasting01:14

Impression Management Techniques IV: Altercasting

Altercasting is a strategic communication technique in which an individual imposes a specific identity or social role onto another person to influence their behavior and shape the interaction. By presuming a role—such as “responsible leader” or “patient person”—altercasting encourages the target to conform to that identity, often aligning their behavior with the expectations associated with the role. The power of this tactic lies in its subtlety; once a role is assigned, it becomes socially...

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Related Experiment Video

Updated: Jun 26, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Automatic source speaker selection for voice conversion.

Oytun Turk1, Levent M Arslan

  • 1Electrical and Electronics Engineering Department, Bogazici University, Bebek, Istanbul, Turkey. oytun.turk@sestek.com.tr

The Journal of the Acoustical Society of America
|January 29, 2009
PubMed
Summary
This summary is machine-generated.

Selecting the right source speaker significantly impacts voice conversion quality. This study developed an artificial neural network (ANN) to identify optimal source speakers, improving male-to-male voice conversion accuracy.

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Area of Science:

  • Speech Processing
  • Artificial Intelligence

Background:

  • Voice conversion algorithms rely on source speaker selection.
  • Performance is known to vary based on the chosen source speaker.

Purpose of the Study:

  • To evaluate the impact of source speaker selection on voice conversion.
  • To develop an automated source speaker selection algorithm.

Main Methods:

  • Subjective listening tests with 180 source-target pairs.
  • Statistical analysis of similarity and quality scores.
  • Training an artificial neural network (ANN) on acoustical distance measures.

Main Results:

  • Source speaker significantly affects voice conversion performance for both male and female transformations.
  • The ANN-based algorithm achieved high correlation (0.84 for similarity, 0.78 for quality) in male-to-male transformations.
  • Female-to-female transformations showed lower reliability (0.58 correlation).

Conclusions:

  • Source speaker selection is crucial for effective voice conversion.
  • The proposed ANN method shows promise for automated source speaker selection, particularly for male voices.
  • Further research is needed to improve reliability for female voice transformations.