![]() Such reverberant voices are unsuitable for popularly used speech encoding methods such as linear predictive coding or code-excited linear prediction. For example, think about the voice sound reverberations in a high-ceiling cathedral. The echo is more noticeable in large rooms with more reflective surfaces, such as concrete or stone walls. Such continued sound wave reflections build up over time and cause reverberations. How much the voice gets absorbed, dampened, or continues to reflect for multiple iterations depends upon the surfaces’ size, geometry, and material. When a person speaks in a closed room, the sound bounces off all the surrounding surfaces. For example, when an end user is excited and pitching the new idea in an elevated tone with an air conditioner in the background, noise removal retains only the speaker’s voice. With the Noise Removal effect, you can remove different noise profiles from audio streams while retaining the emotional aspects of the speaker’s voice. The distractions around us become a part of our surroundings, like slamming doors, moving furniture, or vacuuming. Maxine’s Audio Effects SDK demo of Noise Removal and Room Echo Cancellation Noise RemovalĪs we have started working from home more, there are many potential noise sources in the background of our calls, such as the sound of keystrokes or the compressor of an air conditioner. The Maxine Audio Effects SDK enables you to integrate noise removal, and room echo removal features for narrowband, wideband, and ultra-wideband audio into your applications. Build applications with no background noise or room echo All are demonstrated with prebuilt sample applications. ![]() In this post, you learn how to build high audio-quality applications using containers on Linux or SDK on Windows platforms. With the Audio Effects SDK, you can remove virtually any type of noise, including room echo, and build applications that enable easy-to-understand conversations and productive meetings. NVIDIA Maxine offers an easy-to-use Audio Effects SDK with AI neural network audio quality enhancement algorithms to address poor audio quality in virtual collaboration and content creation applications. ![]() Moreover, a user could talk in a large room that amplifies echoes. ![]() Various background noises can disrupt communication, ranging from traffic and construction to dogs barking and babies crying. With audio and video streaming, conferencing, and telecommunication on the rise, it has become essential for developers to build applications with outstanding audio quality and enable end users to communicate and collaborate effectively. ![]()
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