What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Artificial intelligence
His primary scientific interests are in Multimedia, Electronic media, Audio signal, Audio signal processing and Device status.
His work deals with themes such as Event, Audio feedback and Human–computer interaction, which intersect with Multimedia.
His work on Audio signal flow as part of general Audio signal research is frequently linked to Media management and Set, thereby connecting diverse disciplines of science.
His research brings together the fields of Speech recognition and Audio signal processing.
His Device status study which covers Display device that intersects with Electronic engineering.
His Matrix mixer study integrates concerns from other disciplines, such as Computer hardware, Host processor, Isolation, Power usage and Embedded system.
His most cited work include:
- Tactile feedback in an electronic device (385 citations)
- Electronic Devices with Voice Command and Contextual Data Processing Capabilities (373 citations)
- Techniques for improved playlist processing on media devices (230 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Audio signal, Speech recognition, Computer hardware, Microphone and Audio signal flow.
His study in Audio signal is interdisciplinary in nature, drawing from both Electronic engineering, Artificial intelligence, Computer vision and Noise.
His studies deal with areas such as Ambient noise level, Process, Loudspeaker and Noise measurement as well as Speech recognition.
His work carried out in the field of Computer hardware brings together such families of science as Presentation, Data file, Power consumption, Real-time computing and Electronics.
The study incorporates disciplines such as Headset, Mobile device and Accelerometer in addition to Microphone.
His study focuses on the intersection of Computer network and fields such as Asset with connections in the field of Multimedia.
He most often published in these fields:
- Audio signal (27.59%)
- Speech recognition (26.44%)
- Computer hardware (21.84%)
What were the highlights of his more recent work (between 2013-2020)?
- Microphone (19.54%)
- Signal (12.64%)
- Speech recognition (26.44%)
In recent papers he was focusing on the following fields of study:
Aram Lindahl spends much of his time researching Microphone, Signal, Speech recognition, Audio signal and Process.
The Microphone study combines topics in areas such as Audio signal processing, Beamforming, Headset and Accelerometer.
His Signal research is multidisciplinary, relying on both Field of view, Artificial intelligence, Computer vision, Noise and Mobile device.
His Speech recognition study incorporates themes from Noise, Ambient noise level, Colors of noise, Noise measurement and Rendering.
Aram Lindahl does research in Audio signal, focusing on Audio signal flow specifically.
His biological study spans a wide range of topics, including Object, Echo and Code.
Between 2013 and 2020, his most popular works were:
- Multi-Microphone Speech Recognition Systems and Related Techniques (71 citations)
- Microphone partial occlusion detector (46 citations)
- System and method of improving voice quality in a wireless headset with untethered earbuds of a mobile device (32 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Artificial intelligence
Microphone, Speech recognition, Audio signal, Audio signal flow and Vibration are his primary areas of study.
His research combines Headset and Microphone.
Aram Lindahl interconnects Microphone array, Beamforming and Recognition system in the investigation of issues within Speech recognition.
His work investigates the relationship between Audio signal and topics such as Noise floor that intersect with problems in Audio signal processing, Phantom power, Noise-canceling microphone, Noise and Audio crossover.
His research integrates issues of Matrix mixer, Audio over Ethernet, Telecommunications network and Speech coding in his study of Audio signal flow.
His work in Vibration covers topics such as Voice activity which are related to areas like Detector.
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