In order to save costs and time, the frequency of face-to-face meetings or meetings in business and personal life is no more than before. Mobile phones and Internet telephony (VoIP) have become the driving force behind such important changes in how people communicate with each other. In terms of voice communication, it is important to ensure a good user experience, sound quality and noise suppression.
Today, people rarely experience true silence, and we have become so used to noise that most people don't even notice the presence of noise. The human brain performs very well in filtering out the sounds that are heard, and can hear all the sounds, but only pay attention to the sounds of interest. However, the world has become more and more noisy, using mobile phones, laptops and webcams to make more and more voice communication, it is more difficult to filter out all the noise.
Due to the rapid advancement of electronic technology, there are several methods and potential solutions to manage noise and improve speech intelligibility. In fact, it is now in the midst of a boom in the launch of many new programs. The effectiveness of different scenarios may vary widely, and in most cases, statements about clear and good communication effects are treated in a comprehensive manner. For a given application, it is easy to clearly describe the comparison of one solution to another, but it is difficult to do.
For example, the value of a technical solution designed to enhance the communication capabilities of laptops is highly relevant to where laptops are expected to be used. Using a netbook for Skype calls requires the netbook to pick up only the user's voice and suppress background noise. Students who use the same netbook to record the content of the lecture want to effectively pick up the speech from any ambient noise in the lecture hall. For a given scenario, it may be judged to be valid in some cases, but not in others. The compromise solution may be sub-optimal in both respects, but it provides value for both types of users.
It is already difficult to port a prior art solution to a use case, but it may be more challenging to effectively interpret audio differences at the retail level, as the marketing materials for all products on the shelf may claim to have "excellent audio". performance". Since retail store salespeople are able to provide very few audio presentations, consumers' initial purchases are often random.
Comparison of noise reduction techniquesTechnologies that provide noise reduction schemes can be divided into three categories: electroacoustics, analog, and digital.
Electroacoustic solutions involve the design of microphone components, the selection and placement of these microphones in the relevant acoustic design of the product and microphone placement. Noise reduction or differential pressure microphones are simple examples of inexpensive solutions that provide appropriate advantages in some situations. A good electro-acoustic design is critical to achieving good performance on any voice communication device, but can further increase the underlying performance by using more of the latest digital and analog circuits.
The analog approach involves some direct processing of the electrical signals generated by the microphone or microphone array, such as compression or directed "time of arrival" (TOA) class processing, which may be more efficient because they eliminate the digital conversion segment. However, manufacturing variations inherent in semiconductor processes can directly affect the performance of analog solutions in a manner that is intentionally avoided by digital processes. As analog solutions become more complex and try to provide more value, the performance differences between each process step will match every step that follows. This essentially keeps any successful analog audio product relatively simple. The analog solution also lacks the functional flexibility that a digital solution may have, because the analog system applies (signal) processing in the silicon design itself, rather than on the software layer in a flexible manner.
Digital solutions involve sampling or quantifying electrical signals originating from a microphone, thereby enabling a computer processor to apply a repeatable algorithm to process the signal. The signal is then transmitted or reconstructed in digital form for conversion to an enhanced analog reproduction of the captured speech. Since digital solutions seem to have many inherent advantages under today's silicon technology, it is not surprising that most of the solutions on the market fall into this category.
Digital solutions can implement any algorithm to reduce noise or improve the quality of the voice picked up by the microphone. Typically, these algorithms include spatial selection (where the speech comes from), time domain selection (when or not there is speech), and frequency domain selection (whether the speech frequency is above or below noise). Some programs focus on only one of these aspects, but the best solution will combine all of these aspects, and other improved features may be added in the form of gain control, advanced environment modeling, or other concepts.
One solution relies heavily on airspace selection, ie, direcTIonal processing, which is well suited for applications or applications where the distance of the speaker relative to the microphone is known. This method is used in laptops and mobile phones, but it also has inherent disadvantages while providing advantages. In a laptop, this scene is great for video calls, and sound pickup is limited to the camera direction, but it does not support the use of laptops for conference calls where several people sit around the table. On the mobile phone side, the position of the speech is usually strictly limited, so as to provide significant environmental noise reduction, but it also means that if the phone is not in the right position, the call voice will be reduced.
In contrast, the class scheme relies on statistics of people's speech, continuously and instantaneously determines which speech should be retained and which should be filtered out as noise, and this scheme can effectively cope with a wider range of uses. Disadvantageously, the decisions made by these schemes to distinguish between speech and noise are not always very accurate. The more they are adjusted, the more distortion the user feels. Because of the misclassification, some speeches are filtered out. Normally, the comprehensibility of speech is maintained, but the fidelity is compromised. On the mobile side, this may have little impact because wireless networks have reduced the fidelity of sound, but in other applications such as recorders, fidelity may be crucial.
The best digital solution is usually a hybrid algorithm that takes a part of the various methods and cleverly combines them. These methods can often be adapted to different situations, but often add a heavier burden, adapting or customizing more complex algorithms for various product designs.
Engineers who choose a technical solution to improve the voice quality of their products must also consider the impact on product design in addition to the audio performance of a given solution. Some solutions require a special microphone type, or require a specific microphone layout and acoustic design that may compromise the overall industrial or mechanical design of the product. Some solutions may consume a lot of battery power in a portable device or may not fit into the space available on a printed circuit board (PCB). And in almost every design, developing design costs can be a decisive factor.
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