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 word, enhancing accessibility and user engagement for content creators. These tools are crucial for businesses aiming to reach auditory learners and those with reading difficulties.Text-To-Speech Services provide an efficient way to create natural-sounding audio outputs using advanced AI-driven algorithms. They are widely used in applications like virtual assistants, customer support, and educational tools, making digital content...
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.