What is Azure Speech Cognitive Services?
Azure Cognitive Services Speech is a collection of APIs that enable developers to add speech capabilities to their applications. With features such as speech-to-text, text-to-speech, speech translation, and speaker recognition, developers can create natural and engaging interactions with their users. These services are easy to integrate and can be used to build a wide range of applications, from voice-enabled assistants to real-time transcription and translation. With Azure Cognitive Services Speech, developers have the power to bring their ideas to life and create truly innovative experiences for their users.
The available APIs are:
- Speech-to-Text: Quickly and accurately transcribe in more than 100 languages and dialects. Enhance the accuracy of your transcriptions by creating a custom speech model that can handle domain-specific terminology, background noise, and accents.
- Text-to-Speech: Build apps and services that speak naturally with more than 400 voices across 140 languages and dialects. Create a customized voice to differentiate your brand and use various speaking styles to bring a sense of emotion to your spoken content.
- Speech Translation: This service allows developers to translate speech from one language to another in real-time.
- Speaker Recognition: This service allows developers to verify the identity of a person based on their voice. It can be used to authenticate users for secure access to applications.
GIF - Demo of real-time transcription
How can any of these services help you in your business?
Democratization of AI has been a trend in the past few years & is now stronger than ever. Complex AI & ML models are now readily available and allow any business to easily integrate those models in applications, processes, etc. As the technology is now widely available, it is not technology, but your own creativity that limits the value you will be extracting from AI in the next few years. Here is a selection of use cases related to spoken language, that could drive value for your organization.
Some concrete example use cases:
- A call center could be helped by a speech-to-text model that logs all conversations into written text in combination with a text-to-speech model that provides automated responses to FAQ's in the language of choice.
- Create internal tutorials or demos & distribute that demo to different countries by translating it by an understandable AI voice, so that everyone can access your valuable information.
- Help customers all over the world through a central call center by being able to translate speech in real-time from one language to another
- Add an extra layer of security to your sensitive applications through voice authentication (as an alternative for fiddling with an authenticator app)
- Text-to-speech services can be used to generate natural language reports summarizing key risk metrics in the finance industry, making it easier for analysts to understand and assess risk.
- Speech-to-text services can be used to transcribe audio or video recordings of quality control inspections. Text-to-speech services can be used to generate automated reports that summarize the results of the inspections.
- Speech-to-text services can be used to transcribe audio or video recordings of inventory checks, making it easier to track and manage inventory levels.
- Service technicians can explain the problem they are seeing while being nose-deep into the equipment. Through speech-to-text, we can summarize the problem and query the internal database of historical service reports. Once we have a proper solution, the solution can be communicated once again to the service technician through text-to-speech.
So again, your own creativity is your limit!
How can you get started? And what do you need?
To create an end-to-end use case with Azure Cognitive Services Speech, you will need an Azure account and a subscription to the Speech service. Once you have these set up, you can access the APIs and start building your application. You can use the Speech SDK or REST APIs to integrate speech capabilities into your application. Depending on the specifics of your use case, you may also need to use other Azure services such as Azure Storage for storing audio files or Azure Functions for processing data. Additionally, you may want to use other Cognitive Services such as Language Understanding (LUIS) or Text Analytics to enhance the capabilities of your application. It’s important to carefully plan and design your use case to determine which Azure resources you will need to achieve your desired outcome.
Azure data platform example
This proposed solution uses Azure Speech Services to transcribe calls and then run full-text searches, detect sentiment and language, and create custom language and acoustic models.
What does it cost?
As it is a cloud service, you pay as you go. Here are some numbers to give you an idea on the cost aspect:
- Speech to text: ~€1 per audio hour
- This means that supporting your call center with 5 people during business hours would cost ~ €800 per month
- Text to speech: ~€15 per 1million characters or ~ €15 for 400-500 A4 pages of text.
- Speech translation: ~€2,2 per audio hour
- Speaker recognition: ~ €4-9 per 1000 transactions
As you can see, it's important to manage your costs properly as cost can go up quite quickly if not set up properly. On the other hand, for a limited cost, you have a powerful solution at hand which you could never achieve by creating things yourself.
How to get started?
Do you think you have an interesting use case that could make use of the Azure Speech Cognitive Services? Do not hesitate to reach out and let's discuss how it would practically work in your environment.
Stay tuned for the next post on the Azure Language Cognitive Services!