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Which AI chips hold the better noisy algorithm in noisy cancellation ?
NVIDIA: NVIDIA's GPUs (Graphics Processing Units) are widely used in AI applications, including noise cancellation. With their powerful computational capabilities, NVIDIA GPUs can handle complex AI algorithms for noise reduction and provide excellent performance in tasks such as speech enhancement and audio denoising.
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WTM2101 chips have howling suppression and noisy cancellation functions, especially in noisy cancellation. The latency is less than 10ms，PESQ achieves 3.12 and STOI achieves 0.97. The noisy algorithm is significantly better than the traditional algorithm.
What is an important sample we need to force in noisy cancellation?
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It's worth noting that obtaining an accurate and representative reference sample is crucial for effective noise cancellation. If the reference sample contains any desired audio signal or if it doesn't accurately represent the background noise, the cancellation process may not be as successful in reducing unwanted noise.
What is an important sample we need to force in noisy cancellation?
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What is an important sample we need to force in noisy cancellation?
In noise cancellation, an important sample that needs to be obtained is the reference or "noise" sample. This sample represents the background noise that is to be canceled out from the desired audio signal.The reference sample should ideally capture only the noise component without any desired audio signal. This reference sample is typically obtained by placing a microphone in close proximity...
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WTM2101 chip in computing in memory structure holds high AI computing power in 100X and low power consumption in 5uA-3mA. WTM2101 uses NN algorithm and traditional algorithm. Compared with a single traditional algorithm, the WTM2101 chip could accurately recognize different noises and input the transparent human voice.
How noisy cancellation plays an important role in the handheld transceiver?
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Noise cancellation in handheld transceivers typically involves the use of digital signal processing algorithms. These algorithms analyze the received audio signal and identify the components that are likely to be noise. Then, they generate an anti-noise signal that is out of phase with the identified noise, effectively canceling it out when combined with the original signal.
How noisy cancellation plays an important role in the handheld transceiver?
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How noisy cancellation plays an important role in the handheld transceiver?
Noise cancellation plays an important role in handheld transceivers to improve the clarity and intelligibility of communication. Handheld transceivers are often used in environments where background noise, such as wind, machinery, or crowd noise, can interfere with the transmitted audio.
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- More easily achieve the customized requirements for ordering different speech languages and keywords. On the other hand, it could be more accurate to recognize the keywords in low latency. WTM2101 fulfilled the request in the applications, due to DNN-HCLG models and NN algorithms.
What is the most important point for speech recognition function?
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What is the most important point for speech recognition function?
The speech recognition function has widely been landing applications to smart devices which need high computing power to support. High computing power and low power consumption are the key requirements for solutions. Witmem company focuses on computing in memory structure, which breaks the memory walls and improves operation efficiency 100 times.
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- Smart home owners can input order words to control the home devices. The behaviour for accuracy and speed is direct distinction for each speech recognition chip solution, WTM2101 can achieve microwatt power consumption and 50 Gops AI computing。
How is speech recognition applied on smart devices？
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How is speech recognition applied on smart devices？
- Smart helmet users can navigate, obtain real-time road conditions, and query public transportation routes through the helmet. These functions rely on the powerful computing in memory architecture and speech recognition function in the intelligent helmet.
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- With computing in memory structure, the memory wall has been broken, computing and memory exists in one unit, improving AI computing and lower power consumption. WTM2101 is the CIM chip which has been applied to intelligent voice and intelligent health. Speech recognition is the significant function in WTM2101 and has been widely used in smart wearable devices.
Speech Recognition: HCLG&DNN with computing in memory architecture？
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Speech Recognition: HCLG&DNN with computing in memory architecture？
Adopt the NN acoustic models and HCLG language models . With the hybrid structure, on the one hand , this model can fully use this open source for training and, on the other hand, contribute to the hybrid structure, customers can easily achieve the customized keywords recognition. Meanwhile , computing in memory architecture will improve operation efficiency 100 times.
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ZhiCun Lecture & Peking University | AI big models bring changes to Computility Base
On the evening of April 28, 2023, the ninth "ZhiCun Lecture" of the School of Information Science and Technology, as well as the Frontier of Information Science and Technology and Industrial Innovation Course, was successfully held in Room 106 of the Science Teaching Building. Mr. Wang Shaodi, founder and CEO of ZhiCun Technology and Peking University alumnus, was invited to give a talk on the...
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Computing in memory chips can significantly reduce power consumption, improve battery life, and are suitable for scenarios such as mobile devices that require long-term use. At the same time, it can also reduce power losses.
What are the advantages of storage-computing integrated chips compared to traditional chips?
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What are the advantages of storage-computing integrated chips compared to traditional chips?
Computing in memory chips has higher integration and faster data transfer speeds, which can implement computing and storage functions on the same chip, avoiding data transmission between different chips and improving data processing efficiency. WTM2101 from Witmem adopts computing in memory architecture, improving computing efficiency hundreds of times, with faster read-write speeds and higher...
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Computing in memory chips can be applied to the field of artificial intelligence (AI) to accelerate the training and inference of deep learning algorithms, thereby improving AI performance and efficiency. WTM2101 from Witmem can be applied to accelerate deep learning algorithms, improving the performance and efficiency of AI applications.
What are the application areas of storage-computing integrated chips?
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- Computing in memory chips can also be applied to data centers and cloud computing environments for storing and processing large-scale data, thereby improving data center efficiency and energy utilization.
What are the application areas of storage-computing integrated chips?
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What are the application areas of storage-computing integrated chips?
Computing in memory chips can be applied to mobile devices such as smartphones, tablets, and smart wearables to accelerate application program processing and improve user experience. For example, WTM2101 from Witmem can be applied to smart wearables to provide low-power, high-performance computing and storage functions.
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What is a storage-computing integrated chip?
Computing in memory chip is a new type of microelectronic component that integrates storage and computing functions in the same chip, achieving higher data processing efficiency and lower energy consumption. For example, WTM2101 from Witmem, is a computing in memory chip based on flash memory , integrating a neural network processor and memory, and achieving low-power and high-performance...