Automatic Gain Control

How does automatic gain control work in audio processing?

Automatic gain control (AGC) in audio processing works by adjusting the gain of an audio signal to maintain a consistent output level. It does this by continuously monitoring the input signal and adjusting the gain accordingly. When the input signal is too low, the AGC increases the gain, and when the input signal is too high, it decreases the gain. This helps to prevent clipping and distortion in the audio signal, ensuring a more balanced and consistent output.

How does automatic gain control work in audio processing?

What are the benefits of using automatic gain control in video production?

The benefits of using automatic gain control in video production are numerous. AGC helps to maintain a consistent audio level throughout a video, even when there are fluctuations in the input signal. This can be particularly useful in situations where the audio source is moving or the volume levels are unpredictable. AGC also helps to reduce the need for manual adjustments during filming, saving time and ensuring a smoother production process.

SPS BSI Webinar: MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology

Date: 31 May 2024 Time: 1:00 PM ET (New York Time) Presenter(s): Dr. Elisabetta C. del Re Meeting information: Meeting number: 2632 269 5821 Password: hPFwSbt7H36 (47397287 when dialing from a phone or video system) Join by phone: +1-415-655-0002 US Toll Access code: 263 226 95821 Join us Friday, May 31st, 2024, at 1:00 PM ET for an exciting virtual talk by Dr. Elisabetta C. del Re entitled: “MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology” as part of the activities of the Brain Space Initiative, co-sponsored by the Center for Translational Research in Neuroimaging and Data Science (TReNDS) and the Data Science Initiative, IEEE Signal Processing Society. Abstract MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology Background/Objective. Enlarged lateral ventricle (LV) volume and decreased volume in the corpus callosum (CC) are hallmarks of schizophrenia (SZ). We previously showed an inverse correlation between LV and CC volumes in SZ, with global functioning decreasing with increased LV volume. This study investigates the relationship between LV volume, CC abnormalities, and the microRNA MIR137 and its regulated genes in SZ, because of MIR137’s essential role in neurodevelopment. Results: Increased LV volumes and decreased CC central, mid-anterior, and mid-posterior volumes were observed in SZ probands. The MIR137-regulated ephrin pathway was significantly associated with CC:LV ratio, explaining a significant proportion (3.42 %) of CC:LV variance, and more than for LV and CC separately. Other pathways explained variance in either CC or LV, but not both. CC:LV ratio was also positively correlated with Global Assessment of Functioning, supporting previous subsample findings. SNP-based heritability estimates were higher for CC central:LV ratio (0.79) compared to CC or LV separately. Discussion: Our results indicate that the CC:LV ratio is highly heritable, influenced in part by variation in the MIR137-regulated ephrin pathway. Findings suggest that. Biography Elisabetta del Re is an Assistant Professor of Psychiatry at Harvard Medical School and Principal Investigator of NIMH funded research. She has multidisciplinary training in basic science, mental health, neuroimaging, including electrophysiology, and genetics. She holds a MA and PhD in Biochemistry and Experimental Pathology from Boston University; A MA in Mental Health from BGSP. Dr. del Re’s interest is in understanding psychosis and other serious mental illnesses, by looking at the genetics informing neural processes. Recommended Articles: Blokland, Gabriëlla Antonina Maria, et al. "MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in lateral ventricles and corpus callosum volume." International Journal of Clinical and Health Psychology 24.2 (2024): 100458. (Link to Paper) Heller, Carina, et al. "Smaller subcortical volumes and enlarged lateral ventricles are associated with higher global functioning in young adults with 22q11. 2 deletion syndrome with prodromal symptoms of schizophrenia." Psychiatry Research 301 (2021): 113979. (Link to Paper)

Posted by on 2024-05-29

(ICME 2025) 2025 IEEE International Conference on Multimedia and Expo

Date: 30 June-4 July 2025 Location: Nantes, France Conference Paper Submission Deadline: TBD

Posted by on 2024-05-28

Distinguished Lecture: Prof. Woon-Seng Gan (Nanyang Technological University, Singapore)

Date:  7 June 2024 Chapter: Singapore Chapter Chapter Chair: Mong F. Horng Title: Augmented/Mixed Reality Audio for Hearables: Sensing, Control and Rendering

Posted by on 2024-05-21

Distinguished Lecture: Prof. Dr. Justin Dauwels (TU Delft)

Date: 4-5 November 2024 Chapter: Tunisia Chapter Chapter Chair: Maha Charfeddine Title: Generative AI

Posted by on 2024-05-21

Call for Proposals: IEEE MLSP 2026

Submission Deadline: 15 August 2024 IEEE Signal Processing Society’s Machine Learning for Signal Processing Technical Committee (MLSP TC) is soliciting proposals from researchers interested in organizing the 2026 MLSP Workshop. The MLSP Workshop is a four-day workshop and will include tutorials on the first day. Proposing teams are asked to create a proposal that follows the following outline: Location and Venue: Give an idea on the venue size and facilities. Conference Dates: Ensure they do not conflict with major holidays, or other SPS conferences and workshops. Typically, the workshop is held during the period of mid-September to mid-October. Organizing Committee Members: Build the organizing committee considering factors including (a) active SPS members; (b) diversity in geographical, industry and academia, age, and gender; (c) conference and/or workshop experience; (d) event management experience. For examples, refer to the MLSP Workshops page. Technical Program: Consider the overall structure and conference model; innovative initiatives; student and young professional initiatives; and industry-participation/support initiatives. Budget including registration fees. Hotels in the area that cater to different attendee budget levels. Travel and transportation between the nearest airport and the conference venue. Any other relevant information about the venue or the organization. The intention letter deadline is August 1, 2024, and the deadline for submission of proposals is August 15, 2024. Please submit your proposal to the MLSP TC Chair, Wenwu Wang, and the MLSP Workshop Sub-Committee Chair, Roland Hostettler, via email. We encourage you to contact them with questions or to obtain further details about the content of the proposals. Proposals will be reviewed by the MLSP TC, and the selection results will be announced in October 2024.  

Posted by on 2024-05-21

Can automatic gain control be adjusted manually for more precise control?

Automatic gain control can be adjusted manually for more precise control in some audio processing equipment. While AGC is designed to work automatically, there are instances where manual adjustments may be necessary to fine-tune the gain levels. This can be especially useful in situations where the automatic settings are not producing the desired results or when a more customized approach is needed for a specific audio recording.

Can automatic gain control be adjusted manually for more precise control?

How does automatic gain control impact the quality of a radio signal?

Automatic gain control can impact the quality of a radio signal by helping to maintain a consistent audio level, even when the input signal is weak or fluctuating. This can improve the overall listening experience for radio listeners by reducing the chances of sudden volume changes or distortion. However, excessive use of AGC can also lead to a loss of dynamic range in the audio signal, affecting the overall quality of the broadcast.

What are the potential drawbacks of relying on automatic gain control in sound engineering?

While automatic gain control can be beneficial in many audio processing applications, there are potential drawbacks to relying on it too heavily in sound engineering. One of the main drawbacks is that AGC can introduce unwanted noise or artifacts into the audio signal, especially when the gain adjustments are too aggressive. Additionally, AGC may not always be able to accurately distinguish between desired audio signals and background noise, leading to inconsistencies in the output.

Voice Over LTE (VoLTE)

What are the potential drawbacks of relying on automatic gain control in sound engineering?
How does automatic gain control differ from manual gain control in photography?

Automatic gain control differs from manual gain control in photography in that AGC adjusts the gain of an audio signal automatically, while manual gain control requires the user to make adjustments manually. In photography, manual gain control is often preferred for more precise control over the exposure levels of an image, allowing the photographer to adjust the settings based on their specific needs and preferences. AGC, on the other hand, is more commonly used in audio processing to maintain a consistent output level.

Applications of Digital Audio Signal Processing in Telecommunications

Are there specific industries or applications where automatic gain control is particularly useful?

Automatic gain control is particularly useful in industries or applications where maintaining a consistent audio level is crucial, such as broadcasting, live sound reinforcement, and video production. In broadcasting, AGC helps to ensure that the audio signal remains at a constant level, even when switching between different sources or programs. In live sound reinforcement, AGC can help to prevent sudden volume changes during a performance, providing a more seamless listening experience for the audience. Overall, automatic gain control plays a valuable role in various industries where audio processing is essential.

Are there specific industries or applications where automatic gain control is particularly useful?

Audio quality assessment in telecommunication systems can be conducted using various methods such as objective measurements, subjective evaluations, and perceptual models. Objective measurements involve analyzing parameters like signal-to-noise ratio, frequency response, and distortion levels to quantitatively assess audio quality. Subjective evaluations, on the other hand, rely on human listeners to provide feedback on perceived audio quality through methods like Mean Opinion Score (MOS) tests. Perceptual models use algorithms to simulate human auditory perception and predict how listeners will perceive audio quality based on factors like codec performance and network conditions. By combining these methods, telecommunication systems can ensure high-quality audio transmission for optimal user experience.

The impact of packet-switched networks on audio signal quality can vary depending on various factors such as network congestion, packet loss, latency, and jitter. Packet-switched networks break down audio data into smaller packets for transmission, which can lead to packets arriving out of order or being lost altogether. This can result in degraded audio quality, including issues such as distortion, dropouts, and delays. Quality of Service (QoS) mechanisms can help prioritize audio packets to minimize these issues, but the overall impact on audio signal quality in packet-switched networks is still a concern for applications requiring real-time, high-fidelity audio transmission. Additionally, factors such as network bandwidth, codec efficiency, and error correction techniques can also influence the overall audio quality in packet-switched networks.

The function of an audio packet jitter buffer in VoIP systems is to mitigate the effects of network congestion and variability in packet arrival times, ensuring a smooth and consistent audio stream during voice calls. By temporarily storing incoming audio packets and releasing them at a steady rate, the jitter buffer helps to minimize packet loss, delay, and distortion. This buffer also plays a crucial role in synchronizing audio packets to maintain the quality of the voice communication. Additionally, the jitter buffer can adapt dynamically to changing network conditions, adjusting its size and delay parameters to optimize performance. Overall, the jitter buffer is an essential component in VoIP systems that enhances the reliability and quality of voice transmissions over IP networks.

Audio latency in interactive telecommunication applications is managed through a combination of techniques such as buffer size optimization, jitter buffering, packet prioritization, and codec selection. By adjusting the buffer size, developers can minimize the delay between audio input and output. Jitter buffering helps smooth out variations in packet arrival times, reducing latency spikes. Packet prioritization ensures that audio packets are given precedence over other types of data, further reducing latency. Additionally, selecting efficient codecs can help minimize the processing time required for encoding and decoding audio data, ultimately improving overall latency performance in interactive telecommunication applications.

Speech synthesis technology enhances telecommunication services by providing a more efficient and personalized communication experience for users. By utilizing advanced algorithms and natural language processing capabilities, speech synthesis technology can convert text into spoken words with high accuracy and natural-sounding voices. This allows for the creation of interactive voice response systems, virtual assistants, and voice-enabled applications that can assist users in various tasks such as making calls, sending messages, and accessing information. Additionally, speech synthesis technology enables real-time translation services, voice biometrics for security purposes, and improved accessibility for individuals with disabilities. Overall, the integration of speech synthesis technology in telecommunication services enhances user engagement, streamlines communication processes, and improves overall customer satisfaction.