What is our primary use case?
We use IBM Watson Text To Speech extensively with our systems.
IBM Watson Text To Speech provides exceptional functionality because many of our customers are using it for conversational AI. They are using ChatGPT's LLM model API and integrating it with text-to-speech. This enables healthcare calls, for example, reminder calls from healthcare providers to remind patients about taking certain tablets on specific dates or having appointments on particular days. Calls are routed from Twilio, from the phone call to text-to-speech to ChatGPT LLM. This use case is rapidly growing currently, and we are serving numerous customers in that space.
We have IBM Watson Text To Speech integrated with various AI services. We also offer text-to-speech APIs and speech-to-text APIs to our customers, enabling them to use these services for their CRM operations or content creation.
What is most valuable?
Watson's voice quality is exceptional, and the SSML tags for speed and pitch control are particularly useful. The documentation is comprehensive, making it easy to understand and integrate with our Node.js-based platform.
One suggestion would be to add more voices to IBM Watson Text To Speech. This would be beneficial for pushing new voices as many customers are seeking specific voices for particular use cases, such as movie trailers or news reading.
What needs improvement?
There aren't many improvements needed; however, adding more voices would be beneficial. Regarding pricing, Google or Amazon Polly offer services at $16 per million characters, while IBM Watson Text To Speech is priced at $20 per million characters. Matching these competitive prices would be advantageous.
For how long have I used the solution?
We began using IBM Watson Text To Speech in 2020, and since then we have continued to use their services. Their neural voices are of exceptional quality.
How are customer service and support?
The IBM Watson Text To Speech technical support team provides good service. I have an account manager from IBM who handles most queries. Response times vary from one to seven days depending on the query and priority level.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
When comparing IBM Watson Text To Speech with Google or other providers, the differences are minimal. We also have our own models which perform quite effectively. We invested significantly in R&D as a voice maker. We excel particularly in Indian languages, such as Hindi and Punjabi.
Which other solutions did I evaluate?
IBM Watson Text To Speech offers good value at its price point, but competitor pricing affects our ability to promote it extensively. Users often prioritize pricing, which leads them to choose Google's Text-to-Speech instead of IBM's solution.
What other advice do I have?
The overall rating for IBM Watson Text To Speech is 8 out of 10.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
IBM
