Last year in July, Google launched a new product to add more value to the business out of their contact centers.
This new release of Google is called Contact Center AI which uses many powerful Google machine learning tools to build virtual agents and provide assistance to human agents in their jobs.
Google is releasing various updates of this product that will help to develop a speech recognition characteristic of the product.
Following that, Google mentions that the automated speech recognition service of this product has high accuracy rates.
In this article, we are going to discuss the new update of Google Speech Tech in brief.
Google Speech Tech Update: An Overlook
Previously, many users have complained about noisy phone lines on their latest unplanned online purchase.
To decrease these numbers, Google is launching a feature called Auto Speech Adaptation in Dialog Flow. Basically, a Dialog Flow helps to build better bots.
This tool is used for building conversational interfaces. The Auto speech Adaptation adds context to conversations which help to understand a live person or virtual agent and improve accuracy.
Apart from this, Google has launched another model which is a part of a telephone model. It helps to give quick utterances which are now 15% accurate for US English. A number of other updates are effective and boosts transcription accuracy.
The best part of all is that these updates make the instructions easier which give allowance for endless audio streaming to the Cloud Speech-to-Text API which previously had a 5-minute limit.
A Comprehension of Contextual Virtual Agents
Dialog Flow enhances speech recognition in virtual agents. Automated speech recognition is an essential part of virtual agents but it is tough to do well in noisy phone lines than Lab. However, it will not provide you any positive customer experience.
To aim at issues, Google is upgrading Dialog Flow with Auto Speech Adaptation. This update is quite capable to present robust contextual information of the virtual agent.
Whenever a customer mentions “mail” to return a product, this update helped the user to easily determine the utterance. To make virtual agents more contextually aware, speech adaptation is a great process to learn.
Many product managers define that Dialog Flow helps virtual agents to comprehend context by accounting for all training phrases, entities, and other agent-specific information.
This is possible with Auto Speech Adaptation only. To activate this feature, you need to click on the “Enable Auto Speech Adaption” button from the default offsetting.
With more than 10,000 employees, Auto Speech Adaptation is becoming the largest retailer in Australia.
Woolworths along with Google formed a virtual agent solution based on DialogFlow and CCAI which provides a market-leading performance from the very beginning.
This new invention has many benefits which include an understanding of the format of complex entities like “150g” for 150 grams, identification of brand names, the accuracy of long sentences and others.
On the top, Auto speech Adaptation showed the main development and even permitted to answer more customer queries.
The best part is that earlier it took a long time to build a high-quality IVR experience but now it takes a few weeks to create strong experiences. Apart from that, it made adjustments within minutes.
Accurate Transcription for Human Agents
For the development of Google Cloud Speech to Text, progressing contextual information is at the heart of a trio. However, this is with the help of human agents rather than virtual ones.
The main aim is to make the manual tuning process easier with the use of Speech Context parameters for developers.
The Speech Context updates which are present in beta are classes, expanded phrase limit, boost.
Popular concepts are generally reflected by the pre-built entities delivery. This provides information which is contextual and enables cloud speech-to-text.
Moreover, it helps to provide an accurate transcribing speech input.
2. Expanded Phrase Limit
With Expanded phrase limit, developers can use phrase hints which can help to capture words and phrases by the transcription engine.
This process helps in the tuning process. Basically, Expanded Phrase Limit allows developers to optimize transcription which generates thousands of jargon words.
This is another effective feature which is basically used for the adoption of speech strength by most of the developers.
Also, this helps in increasing the likelihood that is captured by Cloud-speech-to-text with certain phrases for transcription.
Along with this, Google made an announcement of Cloud Speech to Text API baseline developments for IVRs and phone-based virtual agents.
Apart from adaptation-related improvements, Google has included MP3 file format within Cloud Speech to Text API which is available in Beta.
We hope this article was helpful enough to provide you complete information regarding Google Speech Tech update.