Technological advancements have been rather impressive in the past few years. Machines, these days tend to make life a whole lot easier. However, some skills are yet to be developed optimally, and one of those is the development of voice agents. As incredible as it sounds, there is still some room for improvement in this area.
In this post, we are going to elaborate on the technologies that are yet to be developed or those that have failed to attain widespread usage.
Enhancing conversational skills
Developers, these days have access to rather powerful technology which makes their task quite convenient. Via conversational agents, it is possible for developers to create a Chatbot which is capable of holding conversations, sending texts and following commands.
Smart speakers have been a step in the right direction as the developers are now more focused on developing conversational interfaces.
Dialogflow's concept of Prebuilt Agents is one option that can make things work. For instance, a generic module can be developed which can talk about the weather at different runtimes.
Semantic Telemetry for Conversational Agents
For any conversational agent to work there needs to be some method via which the agent can be monitored. Various developers are now working to develop some semantic telemetry which will enhance these conversational platforms.
Voice authentication- the need of time
Voice cloning technology is something that warrants a lot of attention. With further development in this technology, the time is not far when one would fail to differentiate between a real human voice and the voice generated by the machine. This can put security at risk since evidence can be tampered with and false videos can be made with disastrous consequences. Therefore, some advancement is needed via which differentiation can be made possible between a human voice and machine voice. While many do not realize why this feature is essential, with time, its importance will come to the forefront.
Machine to machine communication
Machine to machine interaction can get quite a lot of your work done. In vocal computing, the machine talks to a human, the same way it talks to another machine. With further development in data interchange protocols, these machine to machine interactions can exchange data at the frequency which humans would not be able to hear.
What the machine can learn
Let us now talk a bit about new capabilities that the machine can learn.
Automatic speech recognition
This is an existing technology which is yet to be used to its full potential. End to end learning implies that a single learning system leans a specific concept. It is useful as it reduces the extent of human knowledge required for producing an effective system. The system can then work on a broad range of concepts.
Superhuman Vocal Capabilities
Another goal is to attain human equivalence in certain areas to solve various problems. Opportunities are present in enhancing the vocal computing technology such that capabilities of humans are surpassed.
Machine to human dialogue training, speech synthesis and natural language understanding are some other areas where further developments can bring about a revolution.