Battlefield winner Forethought adds tool to automate support ticket routing – gpgmail


Last year at this time, Forethought won the gpgmail Disrupt Battlefield competition. A  $9 million Series A investment followed last December. Today at gpgmail Sessions: Enterprise in San Francisco, the company introduced the latest addition to its platform called Agatha Predictions.

Forethought CEO and co-founder, Deon Nicholas, said that after launching its original product, Agatha Answers to provide suggested answers to customer queries, customers were asking for help with the routing part of the process, as well. “We learned that there’s a there’s a whole front end of that problem before the ticket even gets to the agent,” he said. Forethought developed Agatha Predictions to help sort the tickets and get them to the most qualified agent to solve the problem.

“It’s effectively an entire tool that helps triage and route tickets. So when a ticket is coming in, it can predict whether it’s a high priority or low priority ticket and which agent is best qualified to handle this question. And this all happens before the agent even touches the ticket. This really helps drive efficiencies across the organization by helping to reduce triage time,” Nicholas explained.

The original product Agatha Answers is designed to help agents get answers more quickly and reduce the amount of time it takes to resolve an issue. “It’s a tool that integrates into your Help Desk software, indexes your past support tickets, knowledge base articles and other [related content]. Then we give agents suggested answers to help them close questions with reduced handle time,” Nicholas said.

He says that Agatha Predictions is based on the same underlying AI engine as Agatha Answers. Both use Natural Language Understanding (NLU) developed by the company. “We’ve been building out our product, and the Natural Language Understanding engine, the engine behind the system, works in a very similar manner [across our products]. So as a ticket comes in the AI reads it, understands what the customer is asking about, and understands the semantics, the words being used,” he explained. This enables them to automate the routing and supply a likely answer for the issue involved.

Nicholas maintains that winning Battlefield gave his company a jump start and a certain legitimacy it lacked as an early-stage startup. Lots of customers came knocking after the event, as did investors. The company has grown from 5 employees when it launched last year at gpgmail Disrupt to 20 today.


10 minutes mail – Also known by names like : 10minemail, 10minutemail, 10mins email, mail 10 minutes, 10 minute e-mail, 10min mail, 10minute email or 10 minute temporary email. 10 minute email address is a disposable temporary email that self-destructed after a 10 minutes. https://tempemail.co/– is most advanced throwaway email service that helps you avoid spam and stay safe. Try tempemail and you can view content, post comments or download something

Google details AI work behind Project Euphonia’s more inclusive speech recognition – gpgmail


As part of new efforts towards accessibility, Google announced Project Euphonia at I/O in May: An attempt to make speech recognition capable of understanding people with non-standard speaking voices or impediments. The company has just published a post and its paper explaining some of the AI work enabling the new capability.

The problem is simple to observe: The speaking voices of those with motor impairments, such as those produced by degenerative diseases like amyotrophic lateral sclerosis (ALS), simply are not understood by existing natural language processing systems.

You can see it in action in the following video of Google research scientist Dimitri Kanevsky, who himself has impaired speech, attempting to interact with one of the company’s own products (and eventually doing so with the help of related work Parrotron):

The research team describes it as following:

ASR [automatic speech recognition] systems are most often trained from ‘typical’ speech, which means that underrepresented groups, such as those with speech impairments or heavy accents, don’t experience the same degree of utility.

…Current state-of-the-art ASR models can yield high word error rates (WER) for speakers with only a moderate speech impairment from ALS, effectively barring access to ASR reliant technologies.

It’s notable that they at least partly blame the training set. That’s one of those implicit biases we find in AI models that can lead to high error rates in other places, like facial recognition or even noticing that a person is present. While failing to include major groups like people with dark skin isn’t a mistake comparable in scale to building a system not inclusive of those with impacted speech, they can both be addressed by more inclusive source data.

For Google’s researchers, that meant collecting dozens of hours of spoken audio from people with ALS. As you might expect, each person is affected differently by their condition, so accommodating the effects of the disease is not the same process as accommodating, say, a merely uncommon accent.

A standard voice-recognition model was used as a baseline, then tweaked in a few experimental ways, training it on the new audio. This alone reduced word error rates drastically, and did so with relatively little change to the original model, meaning there’s less need for heavy computation when adjusting to a new voice.

The researchers found that the model, when it is still confused by a given phoneme (that’s an individual speech sound like an e or f), has two kinds of errors. First, there’s the fact that it doesn’t recognize the phoneme for what was intended, and thus not recognizing the word. And second, the model has to guess at what phoneme the speaker did intend, and might choose the wrong one in cases where two or more words sound roughly similar.

The second error in particular is one that can be handled intelligently. Perhaps you say “I’m going back inside the house,” and the system fails to recognize the “b” in back and the “h” in house; it’s not equally likely that you intended to say “I’m going tack inside the mouse.” The AI system may be able to use what it knows of human language — and of your own voice or the contest in which you’re speaking — to fill in the gaps intelligently.

But that’s left to future research. For now you can read the team’s work so far in the paper “Personalizing ASR for Dysarthric and Accented Speech with Limited Data,” due to be presented at the Interspeech conference in Austria next month.


10 minutes mail – Also known by names like : 10minemail, 10minutemail, 10mins email, mail 10 minutes, 10 minute e-mail, 10min mail, 10minute email or 10 minute temporary email. 10 minute email address is a disposable temporary email that self-destructed after a 10 minutes. https://tempemail.co/– is most advanced throwaway email service that helps you avoid spam and stay safe. Try tempemail and you can view content, post comments or download something