I'm not familiar with Speaker Diarization. Regarding the custom voice creation feature, we just use their voices, which are fine for our concerns. We haven't used it with Google's ML. However it's coming out of the box to us, we've got enough problems understanding the meaning of the utterance. We don't want to spend money on that if Google can do it. Part of our metrics involves call abandonment and some internal metrics we've developed about understanding what to do in a conversation with an utterance and how that plays with the users. Currently, it's disappointingly bad with complex conversations. Simple queries are easy, but real human conversations need a lot of work with AI support. Their pricing is competitive, but what matters most is that it works. The other competitors don't work well enough for us to consider them. That's just the cost of doing business. Overall rating: 8/10
The voice on Microsoft Text-to-Speech is a little bit better than the voice in Google Cloud Text-to-Speech. Overall, I rate Google Cloud Text-to-Speech ten out of ten.
There is a lot of money to be made in languages. If you manage to create something that's very good with translation, you're going to become very wealthy. I'd rate the solution a seven out of ten.
Text-To-Speech Services convert written content into spoken words, offering a range of voices and languages to enhance accessibility and user engagement.Text-To-Speech technology enables users to convert text into natural-sounding speech, supporting varying degrees of customization, from voice selection to speech speed adjustments. Known for their integration capabilities, these services enhance experiences across platforms.What are the key features of Text-To-Speech Services?
Voice Variety:...
I'm not familiar with Speaker Diarization. Regarding the custom voice creation feature, we just use their voices, which are fine for our concerns. We haven't used it with Google's ML. However it's coming out of the box to us, we've got enough problems understanding the meaning of the utterance. We don't want to spend money on that if Google can do it. Part of our metrics involves call abandonment and some internal metrics we've developed about understanding what to do in a conversation with an utterance and how that plays with the users. Currently, it's disappointingly bad with complex conversations. Simple queries are easy, but real human conversations need a lot of work with AI support. Their pricing is competitive, but what matters most is that it works. The other competitors don't work well enough for us to consider them. That's just the cost of doing business. Overall rating: 8/10
The voice on Microsoft Text-to-Speech is a little bit better than the voice in Google Cloud Text-to-Speech. Overall, I rate Google Cloud Text-to-Speech ten out of ten.
There is a lot of money to be made in languages. If you manage to create something that's very good with translation, you're going to become very wealthy. I'd rate the solution a seven out of ten.