Artificial Intelligence: Speech Recognition and its Applications

This report examines the rise and impact of speech recognition technology, particularly within the realm of artificial intelligence. It explores various applications, including call steering, which improves call handling efficiency and reduces misdirected calls, and translation, which facilitates communication across language barriers. The report highlights the benefits of speech recognition, such as ease of use, speed, and the ability to offer services to a more diverse demographic. It also discusses the technology's effectiveness in various business contexts, including the transformation of IVR menus and providing alternative options for consumers. The analysis further touches upon the potential for increased efficiency in document processing and improved customer service through self-service technologies. Overall, the report emphasizes the valuable contributions of speech recognition to businesses and consumers alike.

Running head: ARTIFICIAL INTELLIGENCE
ARTIFICIAL INTELLIGENCE
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Table of Contents
Speech recognition:....................................................................................................................2
Benefits:.....................................................................................................................................2
Call steering:..........................................................................................................................2
Ease of use and speed:............................................................................................................2
Translation:............................................................................................................................3
Opportunity to Offer Services to a More Diverse Demographic:..............................................3
Effectiveness:.............................................................................................................................3
References:.................................................................................................................................5

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Speech recognition:
The speech recognition has been on the rise as an important and influential
technology for many of the years. This was started in the customer markets with the
consumer service lines which could ask the customers for asking the reason for the using
speech or call instead of the buttons of telephone for selecting an option (Xiong et al., 2018).
The speech recognition technology has been becoming more accessible to both business and
consumer related cases.
Benefits:
The uses of speech recognition programs in business practices are as follows:
Call steering:
To wait in a queue for getting through to one of the operators or the worst till it is
being finally put through to the operators that are wrong, can be so much frustrating for the
consumers. Using the speech recognition technology in handling the capacity of the calls
through over 25% as well as reduced to the misdirected calls by approx 66%.
Ease of use and speed:
Still talking is faster for most of the people than typing or crossing the room for
completing task. This is the reason behind that the speech recognition has been transformed
into the digital assistants by Google, Amazon and Apple. Providing a voice command is one
of the fastest ways for completing a task (Yu & Deng, 2016). This is one of the easiest ways
to say “Ok google, what is the time.” The voice command can be built in more and more of
the smart devices, which means the experience of the consumer is easier as well as the brands
that are from the ease of use.

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Translation:
The speech recognition is allowed for the ease of communication that is between the
people who are from various language basis. The speaking is basically a native language as
well as it is having the power of processing by the software that are related to speech
recognition as well as then it is translated either visually or audibly opens up some of the
opportunities that are new (Chan et al., 2016). It might be helpful for the businesses for
engaging in more of the communications that are meaningful and easier without the
requirement for the translator. This is also having the applications that are potential for the
business centres for helping the travellers for overcoming the barrier of the languages as well
as more access to the information as their requirement.
Opportunity to Offer Services to a More Diverse Demographic:
If one of the business is having the processing of the speech technology that are built
into the products of them as well as the products may be becoming the relevant one to one of
the wider groups of the people (Kim & Stern, 2016). As example, it can be said that many of
the business related applications that are presently needed the ability for all of the users for
using the hands of them for some of the degrees for interacting with the apps.
Effectiveness:
The procedure of the works can be becoming more efficient as the document to be
processed to become shorter. The documents are able to be generated to almost three times.
One of the most notable benefits that can come form the speech recognition technology
which is including the ability of dictation that is provided (Chorowski et al., 2015). The
speaking is basically a native language as well as it is having the power of processing by the
software that are related to speech recognition as well as then it is translated either visually or
audibly opens up some of the opportunities that are new. The speech recognition technologies

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can also make contributions that are not valuable to the companies. The businesses that are
able to provide services to the customers that can earn benefit from the technologies for the
improvement in self services.
The call centres that are challenged continuously to the satisfaction of the consumes
that is balanced with the containment of the cost for applying the technology that is related to
the voice recognition for earning benefits from the advantages that are invaluable for the
technologies (Amodei et al., 2016). Providing a voice command is one of the fastest ways for
completing a task. The features that are offered are as follows:
 It can transform the IVR menus that are so much complicated for systems that are
easy to use.
 This is so much compatible with all of the primary operating system as well as the
speech standards.
 This can also provide one of the alternatives for the consumers who are preferred for
skipping the touch tone menus as well as connecting to the agents.

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References:
Amodei, D., Ananthanarayanan, S., Anubhai, R., Bai, J., Battenberg, E., Case, C., ... & Chen,
J. (2016, June). Deep speech 2: End-to-end speech recognition in english and
mandarin. In International conference on machine learning (pp. 173-182).
Chan, W., Jaitly, N., Le, Q., & Vinyals, O. (2016, March). Listen, attend and spell: A neural
network for large vocabulary conversational speech recognition. In 2016 IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp.
4960-4964). IEEE.
Chorowski, J. K., Bahdanau, D., Serdyuk, D., Cho, K., & Bengio, Y. (2015). Attention-based
models for speech recognition. In Advances in neural information processing
systems (pp. 577-585).
Kim, C., & Stern, R. M. (2016). Power-normalized cepstral coefficients (PNCC) for robust
speech recognition. IEEE/ACM Transactions on Audio, Speech and Language
Processing (TASLP), 24(7), 1315-1329.
Xiong, W., Wu, L., Alleva, F., Droppo, J., Huang, X., & Stolcke, A. (2018, April). The
Microsoft 2017 conversational speech recognition system. In 2018 IEEE
international conference on acoustics, speech and signal processing (ICASSP) (pp.
5934-5938). IEEE.
Yu, D., & Deng, L. (2016). AUTOMATIC SPEECH RECOGNITION. Springer london
limited.