Multimodal interactions: are they breaking through?

Multimodal interactions: are they breaking through?

Multimodal interactions: are they breaking through?

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Last week I watched a webinar and demo by a company providing tools and solutions for conversational customer service. Interactive Media, where I work, is in the same sector and I wanted to scoop out a competitor, see what they have and how they are presenting their solutions to the market. Everyone does this of course; I don’t feel bad about it in the slightest.

This company was presenting with great emphasis a solution that allows a caller to synchronize a voice call (on a smartphone) to a visual IVR component. In essence, when users call, they are offered the option to receive a text message that contains a link to a personalized web application. The web app provides information about what the call is about, and you can navigate it by clicking on the pages, or by voice.

In the demo, this provides a great experience: all the information regarding the case is at the user’s fingertips, and it’s much easier to insert additional data. For instance, think about how hard it is to dictate an email address to an agent (let alone a virtual assistant!). With this type of visual IVR, the user can simply type it into a box, a much more efficient and error-free process.

This particular solution is not simple: you have to use conversational AI to understand what the caller says, being able to identify the intent and navigate precisely by voice, populate the web pages to service the intent on the fly, create and send the link by text message, and, most difficult of all, synchronize the voice and web parts of the session. Well done!

But seeing this demo left me rather surprised: you see, I was doing exactly the same demo with Interactive Media software 5 years ago (and I have the videos to prove it). This made me realize two things. One is that the Interactive Media people and technology are kick-ass, well ahead of most competition. But the other, considering that I was not able to sell this solution, is that sometimes focusing on increasingly sophisticated, “frictionless” services does not pay.

That demo is fantastic, but how many similar applications have you seen in real life? And, based on your real-life experience, how often would you need something similar? In essence, it seems to me that we as an industry are targeting increasingly complex software solutions to an ever-decreasing number of users.

The vast majority of users hope to never have to contact customer service. But when they do it is often for a simple question, one that does not in general need this type of infrastructure. Normally, users can search the company web site, chat with an agent or a chatbot, call in. A good percentage of people calling in does so because they are not comfortable with other channels, either because they are on the move and voice is the best way to interact, or because not everyone is familiar with web technology. Again, as an industry, we tech people tend to project our own experience onto everyone; folks, this is not the entire world!

For people who call in only with voice, there is PhoneMyBot, the Interactive Media service to provide voice channels to chatbots with a no-code, ready to roll approach. Companies that have deployed chatbots but have no conversational AI on the voice channels can use PhoneMyBot to enable telephone conversations with their existing self-service app. Conversational AI vendors who only support textual and web channel can use PhoneMyBot to offer voice channels to their customers. PhoneMyBot targets simpler self-service voice solutions for the vast majority of users.

But if you really need a synchronized voice and Visual IVR application for flashy service to your most tech-savvy customers, why don’t you also call Interactive Media? After all, we have a 5-year advantage.

Please go ahead and try PhoneMyBot for free: contact Interactive Media at info@imnet.com or click the button below.

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PhoneMyBot and ChatGPT: giving voice to AI

PhoneMyBot and ChatGPT: giving voice to AI

PhoneMyBot and ChatGPT: giving voice to AI

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Talking with ChatGPT over the phone is cool. But can we make it useful?

Everybody is talking about Open AI’s ChatGPT, at least among the tech people worldwide. It’s the first large language model chatbot to make a splash, and what a splash! It landed with the energy of the Chicxulub asteroid – the one that killed the dinosaurs 65 million-odd years ago in the Yucatan sea. That asteroid generated a mile-high tsunami, almost as high as ChatGPT. One should go slow with the metaphors though: are ChatGPT and its peers going t kill …[gasp]… us? I am an optimist and I don’t think so, but the jury is out according to much of the press.

In all cases, after using ChatGPT to write poems about pickleball or essays on Tibetan literature, the tech community is trying to understand what it can do for real business.

We at Interactive Media have integrated ChatGPT with PhoneMyBot, our service to provide voice channels to chatbots with a no-code, ready to roll approach. Through PhoneMyBot it is now possible to make a phone call to ChatGPT, ask questions and listen to its answers. This is still only a demo, but in the process we have developed some ideas on whether and how ChatGPT may work for what we do normally, which is providing tools to companies to service their customers.

Let’s say it immediately: without personalization, ChatGPT is not sufficient to implement a customer service voicebot. The domain is too wide: it is literally the whole Internet. This means that ChatGPT cannot use its normal language model to answer pointed questions on – say – your bank balance today.

It is also outdated: according to OpenAI, the version of ChatGPT using GPT-3.5 has limited knowledge of events that occurred after 2021. A new version based on GPT-4 has been released a few days ago, but as time goes by, and since the language model needs to be curated, which take time, very recent events will never be in ChatGPT knowledge base.

To be sure, in customer service there is sometimes a need for general-purpose conversation. In our experience, users sometimes go out on a tangent and ask bots all sorts of questions, for instance: where do you live? how old are you? can I see you? how much are you paid?… ChatGPT has certainly good answers for all these questions, and it would be useful in side conversations. ChatGPT is also language-independent: in essence it can tell what language a user is speaking and answer in the same language. This is a stunning capability and it makes it so much easier to use ChatGPT.

However, it is possible to “fine-tune” ChatGPT for specific domains, adding dozens, hundreds or thousands of examples of specialized prompt-completion pairs that define a separate domain, identified by its own name and id. This domain goes to augment the general-purpose model and allows the chatbot to answer pointed questions. At Interactive Media, we are experimenting with fine-tuning one of the available general purposes models and we’ll keep you posted on how it goes.

There’s another snag though, because to be useful you also need to access actual data related with people’s requests. ChatGPT of course does not perform the appropriate database queries into company databases or CRMs. But Interactive Media is well versed in this matter and can provide a real-time layer to authenticate securely into a company back-end, retrieve the appropriate information, and insert it into the ChatGPT answers. At least partly, this has to be done on a case-by-case basis, so call us to discuss!

Please go ahead and try PhoneMyBot’s connection with ChatGPT: contact Interactive Media at info@imnet.com or click the button below.

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The future of intelligent voice

The future of intelligent voice

The future of intelligent voice

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As the market for smart speakers falters, what are the Big Three (Amazon, Apple, Google) going to do?

Alexa, should I bring an umbrella out tomorrow? This is a question that owners of smart speakers have been asking since 2013, the year when Amazon released its first Echo product. Soon Google and Apple followed suit, with their Google Assistant and Siri technologies.

While Siri is embedded into Apple hardware as a software feature, both Amazon and Google produced and actively started selling the hardware to support their speech software: a line of smart speakers with sensitive microphones that listen for people uttering a key phrase to start detecting what they say. The rise of these devices has been meteoric. They were cheap, convenient, and they largely supplanted both radio and stereo systems in the home, by streaming content controlled by voice. They were sold by the tens of millions, both in the US and around the world: according to a Comscore report, in 2021 almost half of the US internet users owned at least one of them.

Most people in the US are familiar with Alexa: she listens to the sounds around her and when she hears her name she springs into action. This means recording the sentence that comes after the keyword and sending the audio to the Amazon Cloud for recognition, receiving the answer and playing it back. (Supposedly, nothing is recorded outside of the keyword-initiated transaction of course). The same is true for the Google version; hey Google is both longer and less personal.

As an aside, I know someone who’s name is Alexa – and it was her name well before Amazon released the first Echo: I wonder how she feels being called upon doing the biddings of countless people…

The problem with the status quo: lack of revenues

As it often happens in the tech industry, for smart speakers the technology leapt ahead of the profitable use cases. Yes, people were and are using their smart speakers often, but mostly to ask general questions, check on the weather and ask for music streaming. The vendors figured that, with time and as adoption increased, they could come up with a revenue model that would support the business, but so far no-one has managed it.

Of course, there are ads within music streaming if the owner does not subscribe to a music service, but few and far between not to degrade the experience too much. And a $10 a month music subscription is not a panacea to support providing and maintaining the infrastructure for the rest of the service.

The most profitable use case that was hoped for at the beginning, shopping by voice, never took off: people are understandably weary of providing personal information, credit card numbers, etc. to the Cloud through yet another channel, and by definition any shopping done through a smart speaker is “sight unseen”.

So, in the past few months with the changing economy and the realization of how difficult it is to really monetize smart speakers, there has been a definite retrenching by both Amazon and Google. Amazon laid off a good portion of the Alexa development team, Google reportedly greatly reduced funding for the Assistant line and – this is very recent news – Alphabet is laying off as much as 12000 workers in January 2023. One can imagine that the worst-performing divisions would be most affected.

Smart speakers are in trouble.

Voice apps on smart speakers

However, many companies and organizations developed apps to integrate with Alexa and Google Assistant, through the respective APIs. In this case, the smart speakers act simply as a speech transcription and rendering interface: once the app is active, they transcribe what the user says and send the text to the external service, take the text that service sends back and render it into voice for the user to hear.

Amazon calls these apps Skills; Google calls them Actions. Either way, there are hundred of thousands of them. They can be launched with a special prompt: “Alexa, open [skill name]” or “Hey Google, talk to [action name]”. While many apps have not been successful and have minimal use from this channel, others are important or even essential.

What happens to these apps if the smart speaker vendors limit and then terminate their offer? Some are merely activating an additional channel to a wider service, and presumably would not be impacted too severely. But others were developed specifically to take advantage of the voice channel offered for free by smart speakers. For instance, I recently talked with the developer of a skill for blind people, who use their voice to access information that others get from screens. 

Skills and Actions developers are seriously worried.

 On the other hand, what other conduits are there for two-way, intelligent voice applications in the house? Well, the one we’ve always had: the telephone (no matter if fixed or mobile). Granted, calling an app over the phone is a little more complex that simply saying “Hey Google”, but everyone knows how to use a phone and the technology could not be more tried-and-true. The problem then is connecting existing intelligent applications to the telephone network.

PhoneMyBot as the conduit for voice apps

Interactive Media offers PhoneMyBot, a service born to expand the channels available to chatbots to include voice channels. It performs the same functions that are done by intelligent speakers for their apps, transcribing the users’ speech and sending it to the connected application. Then it receives text in return and transforms it into speech, piping it into the voice network. PhoneMyBot is natively integrated into the telephone network and exposes to apps an API equivalent to the ones from Alexa and Google Assistant. In addition, PhoneMyBot integrates with a number of contact center suites to transfer the call to a human agent if necessary.

What makes PhoneMyBot appealing to small organizations that may become stranded if intelligent speakers decline too much? It’s extremely easy to try: an initial trial period is free, and commercial traffic is billed at a (low) per-minute rate independently from the traffic volume. This makes it ideal for low-budget, pay-as-you-go services. The administration is simple and powerful: a single portal provides access to all the traffic data and stats. And its robust, with an infrastructure built on telco-grade software, managing millions of calls per month.

Go ahead, try it! Click the button below.

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My view of Text-to-Speech (TTS) technology evolution in 3 fundamental steps

My view of Text-to-Speech (TTS) technology evolution in 3 fundamental steps

My view of Text-to-Speech (TTS) technology evolution in 3 fundamental steps

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The Author co-founded Interactive Media in 1996 and is the CEO of the company. Interactive Media is a global developer and vendor of speech applications.

Interactive Media has a long history of developing progressively more sophisticated speech applications, with more than 25 years of experience in managing text to speech. But I started working on this even before and I can say that I have been involved in CTI (computer-telephony integration) since its beginning. I want to give a brief perspective of my first-hand experience here.

In 1993 and in the following years I had the privilege to collaborate with the CSELT, the pre-eminent Italian telecommunications lab in Torino. CSELT had then already been working on Text-to-Speech technologies for decades.

Back in the 70s CSELT was, together with AT&T, the only company working on developing TTS for commercial use. Their first publicly demonstrated system was called MUSA. You can hear it speak in this video (in Italian): https://www.youtube.com/watch?v=TvKChDE-Lnk.

In 1993 CSELT released Eloquens, also based on diphones concatenation (diphones are the sounds that we make from the half of a phoneme to half of the next phoneme when we speak a word). Eloquens’ quality was much better than MUSA, and even now it can be considered a good quality product. It is still in use for several applications. See for instance https://www.youtube.com/watch?v=sZuV1L7cqro.

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Record with the nursery rhyme Fra Martino campanaro (Brother John), as sung by MUSA in 1978

Eloquens software had been developed to be used on a stand-alone PC. But CSELT, that was owned by the national telephone company, naturally had the goal to use it on the telephone network. This is where I came in. At that time, I was a consultant for an Italian company that had the exclusive sale rights for Italy of the computer boards made by Natural Microsystems, and American company. These were among the first CTI boards which allowed a PC to communicate with the telephone network.

My role was to adapt the Eloquens software to run with the board’s DSPs, so that it could be used in IVR-type applications. I remember these days as an extraordinary period. Aside from the project, which was very interesting, I was a young engineer just out of university and spending a long period of time away from home for the first time. Torino was at that time a heavily industrial city and at 8:30 pm all restaurants were empty, and no-one was in the streets. The following day the factory sirens would go off before dawn to mark the start of a new working day. This was quite different from my hometown, Roma. I was working with Marcello Balestri and Luciano Nebbia’s group: they were excellent engineers, like most of the staff at CSELT. Together we were then able to develop and release the first Italian version, and one of the first in the world, of a commercial TTS that could be used in an IVR system.

Even today, after 30 years, that software is still deployed in some companies. This is also because only in the past few years there has been a substantial technological leap with noticeably better performance, thanks to the use of neural networks and in particular deep learning techniques. Training neural networks to perform TTS, the process does not rely on diphones concatenation and so it avoids the “pixelation” that is still present in older systems. Using deep learning the prosody is practically perfect, and people can sometime not tell a synthetic voice apart from an original human speaker.

One interesting capability of this technology is the possibility to create one’s own synthetic voice, by recording a few hours of audio, for instance by reading a text. Among the most otherworldly applications is the use of a synthetic voice to create a digital persona for a person, even after that person has passed away.

To speak of more worldly affairs, recently Interactive Media won a contract to produce all the audio responses in TIM Brazil’s customer service systems, using a Neural TTS from Microsoft. The resulting quality is amazing, and the caller has the feeling that the speaker is a person: polite, sympathetic and helpful, while still professional sounding. We at Interactive Media are ready to expand on this experience, with the know-how that we accumulated in 25 years, on all other markets. Please contact us if the voice that you use to talk with your customers is important to you.

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Boosting the development of voice-enabled virtual assistants

Boosting the development of voice-enabled virtual assistants

Boosting the development of voice-enabled virtual assistants

Written by

PhoneMyBot by Interactive Media is a service that transforms chatbots, that work only on text conversations, into voice-enabled virtual assistants. To do this, PhoneMyBot terminates the voice channel – be it a telephone line, a recorded voice message, or other streaming voice channels, transforms the voice into text through a speech-to-text service, and sends the text over to the chatbot.

When PhoneMyBot receives the answer as a text message from the chatbot, it renders it into speech and pipes it back to the user. You can learn more about PhoneMyBot here.

There are many nuances and details that are missing from the description above (some of them are patent-pending), but a key to PhoneMyBot’s success is the ability to integrate with many chatbot platforms. PhoneMyBot offers a standard cloud API that chatbots can use, but it also includes adaptors that use the chatbot platforms’ native API, simulating a simple web client. This way, PhoneMyBot can communicate with existing chatbot deployments without the need for new developments in the chatbot code. At the moment, PhoneMyBot deploys adaptors for about 10 chatbot platforms, but new ones are coming out all the time, depending on our customers’ needs. If you don’t see an adaptor for your platform, let us know and we can add it.

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This service was designed to make it cheap and immediate to add voice to an existing chatbot deployment – and it does that, but as an interesting side effect it also lowers the cost of new voicebot developments, while speeding up their deployment time.

Why is that? It all comes down to the dynamics of the conversational AI market for enterprise customers.

A successful conversational AI project entails more than just software and communications. It needs to be tailored to the company’s workflow, products and services, and lingo. Often, the type of language that needs to be used is not the same as in a general-purpose conversation, and this requires conversational applications to be trained to better support it. Of course, this is a common requirement in this type of project, and conversational AI platforms support language customization. But it still means that project development, testing, refining, and deployment take substantial time and effort.

Now, there are only so many conversational AI vendors offering voice integration, and system integrators who can use their platform to implement projects. In addition to the conversational AI part, a voice-enabled project includes integration with the telephone network or the corporate PBX, insertion into the IVR flow, and integration with the voice path in the contact center – both to forward calls if the virtual assistant cannot service them completely, and to provide call-associated data to human agents to make their work easier and provide better service.

All this requires specialized expertise, which few vendors have. These companies and people are in high demand, so delays can be long and costs high. 

But PhoneMyBot provides a ready alternative, with its pre-integrated voice channels. It includes telephone network and WhatsApp connectivity, and APIs to transfer calls to other voice endpoints (for instance, a contact center queue). Interactive Media has tons of experience integrating with the most common contact center suites both to insert the virtual assistant into the IVR flow and to send data attached to calls to the human agent who is servicing it.

This means that the pool of vendors that can bid on a voice-enabled conversational AI project is suddenly much bigger. Even companies with little or no voice expertise can now deliver a high-quality omnichannel virtual assistant: they only need to test their PhoneMyBot integration and iron out any small wrinkle that the additional channel may create in their conversational application strategy.

There are many more text-only conversational AI offers than voice-enabled ones. PhoneMyBot opens the omnichannel market to them, which benefits vendors, their customers, and ultimately the customer experience that you and I receive when we call a customer service line.

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WhatsApp voice messages and how chatbot can use them

WhatsApp voice messages and how chatbot can use them

WhatsApp voice messages and how chatbot can use them

Written by

WhatsApp lets people record and send voice messages. What does it mean for the chatbot customer experience?

Like most Europeans – well, I should say most people in the world – I am a WhatsApp user. WhatsApp has more than 2 billion users worldwide, about a quarter of all humans. And although WhatsApp’s penetration in the United States is lower than in most places, if you are a foreign-born US resident who wants to keep in touch with friends and family back home, like me, WhatsApp is THE app to use.

WhatsApp offers chats, voice calls, video calls, one-on-one or among ad-hoc or organized groups. It also has a business offer, allowing companies to be messaged or called on WhatsApp to be where their customers are.

This feature was introduced in 2018 and is being used more and more: people appreciate using the same app to communicate with individuals and companies, and many telecommunications vendors resell WhatsApp business numbers and the services that come with them.

While I am a member of a couple of organized groups, I mostly use the app to message my friends or call them directly, rarely involving more than one person at a time. But I noticed a funny thing: some of my friends have stopped sending chat messages altogether. Instead, they use another feature of the app, that lets you record a voice message and send it over in a conversation. I prefer to type and let the autocompletion feature on my smartphone work its magic, also considering that receiving a voice message is certainly less immediate than reading a short text. But I can see several reasons for preferring to send a voice recording.

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For instance, you may be on the go, without the time and place to type. Or you may have troubles seeing the phone keyboard, either because of light conditions or because you can’t see very well (I certainly have problems typing without my reading glasses, I am at that stage of life). You may want to be more expressive using your tone of voice: spoken communication is much better than text to convey feelings. Or you may not be comfortable writing in general – or the person on the other side may have problems reading. For all these reasons, and possibly others that I can’t think of, sending voice messages instead of typing is on the rise.

And this is fine, as long as you communicate with a human who speaks the same language as you. But there is a special use case that is completely destroyed by this habit: communicating with a chatbot. You see, businesses that use WhatsApp to communicate with their customers via text messages often employ chatbots, automatic “conversational AI” attendants that use natural language capabilities to converse with people, understand the reason for the interaction and help them in a more efficient and cheaper way than having a human customer representative on the line the whole time. Except that chatbots can understand WRITTEN communication, and not voice recordings.

Instead, more and more chatbots that connect with WhatsApp receive recorded voice messages. In this case there are two possibilities: the chatbot recognizes that it cannot access the message and dumps the session. Or it transfers the session to a human agent who listens to the message, researches the answer, and writes back. The first case of course brings to an awful customer experience, the second to a substantial increase in costs, as the human agent is doing the job that the chatbot could do, having to listen to sometimes long and rambling messages to extract meaning.

 

What is there to do? Interactive Media, the company where I work, has launched PhoneMyBot, a service that provides an alternative, cheaper and far more elegant solution to the problem. PhoneMyBot was born to expand the channels available to chatbots to include voice channels. It provides a telephone network interface, along with other voice integrations, transcribing the users’ utterances and sending them to the chatbot, and receiving text in return from the chatbot, transforming it into speech, and sending it back to the user over the voice network. PhoneMyBot is completely cloud-based, and also integrates with a number of contact center suites to transfer the call to a human agent if necessary.

In addition, PhoneMyBot integrates with WhatsApp to receive a recorded voice message in a set language from a chatbot, transcribe it, and send it back to the chatbot as text. All the chatbot has to do is communicate with PhoneMyBot’s WhatsApp number to set the language, send the voice file, and receive the transcription. PhoneMyBot also exposes a standard HTTPS-based API for that, which the chatbot can use with a small development effort.

It may be that the primary reason some people use WhatsApp’s recorded voice messages feature is that they have difficulties reading and writing. You may think this is a problem of the past, overcome now everywhere. But not so fast. The latest figures for United States residents put the non-literacy rate at about 1%. The US is in the middle of the pack here: China (3%), Brazil (7%), India (25%) fare a lot worse. (See https://www.macrotrends.net/countries/ranking/literacy-rate for a complete list). The figures for people who have basic literacy but are uncomfortable reading and writing is likely much higher. So, this is a real possibility.

In addition, PhoneMyBot can also convert the text received from the chatbot to speech (with a choice of voices) and send it back to the chatbot to attach to the WhatsApp response message. This way, users who would like to conduct the complete conversation with recorded messages can receive the chatbot’s answer on their preferred channel.

Sometimes useful features in products and services have unintended consequences. I am sure that when WhatsApp introduced their voice messages feature, they were thinking of human-to-human communications only and for this use case it is a great alternative. But it breaks other use cases, like human-to-machine interactions. Fortunately, PhoneMyBot is there to fix it.

You can try PhoneMyBot’s WhatsApp message transcription right now. To get started scan the code below, fire up WhatsApp on your phone and start the interaction with the word “start” as first message. If you type “help”, PhoneMyBot sends you details on how to use the service.

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