V.U.X. World: Recent Episodes
V.U.X. World
Your detailed guide through the voice-first revolution. Turning you into an epic voice user experience designer, developer or all-round, clued-up voice-head. Whether you're an individual, an agency, a brand or a newbie, we'll help you take advantage of the biggest shift in user behaviour since the smartphone.
TalkVia, the voice assistant design and development platform for marketing teams looking to invest in emerging technologies like Alexa and Google Assistant, conducted the Smart Audio Report, Australia, to understand the adoption and usage levels of voice assistant technologies down under.Head of Innovation, Guy Munro, joins us to share the details and insights from the survey, how voice assistant adoption in APAC is similar or different to the US and EU, as well as his perspectives and advice for marketing teams looking to explore these emerging channels.LinksCheck our TalkViaDownload the Smart Audio Report, AustraliaConnect with Guy on LinkedIn See acast.com/privacy for privacy and opt-out information.
Voice AI can provide immense value outside of the home. Problem is, outside is noisy! So how to you create voice AI solutions and speech recognition systems that work well in cars, in traffic, outside or with screaming kids in the background!?We're joined by SoundHound's Director of Business Development, Andrew Richards, to shed some light on how one of the top voice AI companies tackles this challenge.We dive into:What are the common challenges when implementing voice solutions in noisy environments?Any examples of areas where the environment proves trickier than others? Microphone technology, placement and arraysWhat's beam forming and why is it important?How do you (or what do you do to...) mitigate the noise to get a clean signal? About additive noise, convolutional noise, distortion and noise reductionWhat do you need to consider when implementing a voice assistant in a noisy environment? How to train speech recognition systems for use in noisy places?LinksVisit Houndify.comRead the Houndify Speech to Meaning blog (recommended)All about speech recognition with Catherine BreslinHow voice AI is disrupting industries with SoundHound's Mike ZagorsekHow to train speech recognition systems with Atexto See acast.com/privacy for privacy and opt-out information.
It's hard enough designing conversational AI agents that understand single line utterances and are able to string together a conversation with a person. Try monitoring both a caller and an agent having a two way conversation and understanding it to the extend that you're able to offer real time, in the moment, accurate guidance to the call handler.This is exactly what Balto does. We chat to CEO, Marc Bernstein, about where the idea for Balto came from, how he went about creating the company, the business and technical challenges he and the team had to overcome and we get into details on how the Balto solution is helping contact centre agents be more productive.LinksBalto.aiConnect with Marc Bernstein on LinkedIn See acast.com/privacy for privacy and opt-out information.
Have you misunderstood the aims of your digital transformation programme?So much time, money and effort is spent on rebuilding websites, launching apps, managing social media, all to try and prevent customers from calling your contact centre and costing you money.All of this to prevent 'avoidable contact'.Yet, they still call.The question should be 'why don't you want to talk to your customers?' There isn't a better way to foster deeper relationships that to have a conversation.We chat to Speakeasy AI CEO, Frank Schneider, about just that. We find out more about how you can benefit from talking to your customers, and how you can do it without messing about with websites and apps. How you can do it with voice AI.We also chat in detail about Speakeasy AI's patent for Speech-to-Intent technology and how this excels the customer experience of voice AI and conversational automation.This is Frank Schneider's hat trick on VUX World. Our only guest so far to return three times on the show. For the regular listeners of the show, you'll be familiar with Frank's charisma and knowledge already. And for those new to VUX World, you can check out our previous insight-packed conversations with Frank here:All about Speakeasy AI with the Fresh Prince of AI, Frank SchneiderAutomating call centres with voice AI, with Frank SchneiderLinksspeakeasyai.comfrank@speakeasyai.com See acast.com/privacy for privacy and opt-out information.
You might think of Google assistant as the thing that you use to search the web on your phone or the speaker you use to play music at home. But with every new partnership, Google adds another string to its assistant’s bow that sees a slightly different Google Assistant appear on different surfaces. All the while, the Google Assistant umbrella expands and it edges closer to becoming the default assistant in your life and the default access point to the internet.Read the full article See acast.com/privacy for privacy and opt-out information.
We take it for granted that, when we talk to our voice assistants, they hear us. When we dictate a message to Siri, it transcribes it. Speech recognition is used in a whole manner of areas beyond voice assistants, too. Transcribing videos on YouTube, PowerPoint, dictation, call transcriptions in contact centres and beyond. But speech recognition systems don't always perform as expected and require training constantly to address bias, new language and dialects.Why do automatic speech recognition systems need training?There are many cases, however, where speech recognition systems either fail, or need training. For example, training speech recognition models to remove bias is a core priority for all speech recognition providers today. Studies have shownthat the major ASR players technologies perform poorly when used by black people, as compared to white people, for example. Addressing this performance gap is of upmost importance.Another reason for training ASR systems is expansion into other countries and to cater to other languages and accents. When Amazon, for example, aims to launch Alexa in, say, Brazil, it needs to train its speech recognition models in the Brazilian language, dialect and accents. Understanding languages, accents and dialects is a core part of making AI accessible to the world, as well as for commercial expansion.Finally, companies need to continue training ASR systems to make sure that new vocabularies and phrases that enter a given language are understood. Prior to 2020, the world wasn't saying the phrases 'COVID', 'COVID 19', 'SARS COV 2' half as much. A few year's prior, Tik Tok wasn't a thing. Language changes, and so ASR systems need to change with it.In this episodeIn this episode, we chat to Esteban Gorupicz, CEO, and Alejandro Heredia, Technology Business Development and Sales, at Atexto about how they help ASR companies train speech recognition systems and tackle the above problems.About AtextoAtexto is one of the world's leading providers in speech recognition training. It's platform allows ASR providers to crowd source training data for speech recognition systems, label and tag the data, then export it to feed into its models. It also has an ASR benchmarking tool, which allows providers to compare performance across ASR systems.LinksCheck out AtextoFind out about the ASR World Championships See acast.com/privacy for privacy and opt-out information.
Sam Danby of Boost.ai joins us to share how to take your conversational AI to the next level using Boost technology, including creating conversational agents from web content, assessing and choosing the right technology such as ASR and NLU, as well as learning and iterating on language models.LinksFollow Sam on Twitter and connect on LinkedInVisit Boost.ai See acast.com/privacy for privacy and opt-out information.
Voicebots for customer service are in increasing demand, but how do you actually integrate one into a contact centre?Learn how to take an existing chatbot and repurpose it for your contact centre. Many chatbots provide immense value to customers, and many call centres are overwhelmed with demand. Why not offer your chatbot service through your contact centre and help customers self serve, and customer service staff manage demand.Joining us this week is Ilan Avner, Director of Product Management at AudioCodes. Ilan will share how any brand or developer who has existing conversational AI implementations can scale those conversations into ANY contact centre system.We discuss the challenges you'll face when trying to integrate bots into contact centres including how to deal with on-premise vs cloud deployments, security, protocols and standards, timescales and costs. We'll also cover how you can avoid all of the completely by using the AudioCodes Voice AI Connect product.A truly enlightening conversation for anyone who's interested in the practicalities of integrating any kind of bot into contact centres for improving self service and customer experience.LinksCheck out the AudioCodes Voice AI ConnectCatch up on the AudioCodes webinar with VodafoneConnect with Ilan Avner on LinkedIn See acast.com/privacy for privacy and opt-out information.
As much as voice technology has been hyped over the last few years, perhaps leading to some unrealistic expectations, it's beginning to find its feet in reliably and consistently improving customer service in contact centres. Regardless of hype, voice technology has super-human qualities when applied in a customer services environment and especially, according to today's guest Nikola Mrkšić, CEO and co-founder of London-based PolyAI, when using PolyAI technology.We chat to Nikola about what defines 'super-human' qualities for voice assistants, how the PolyAI technology differs from some of the common providers, why drag and drop tools have limitations, and understand Nikola's perspective on the voice industry overall.LinksVisit PolyAIFollow Nikola Mrkšić on Twitter or LinkedInWebinar on multilingual voice assistants See acast.com/privacy for privacy and opt-out information.
Tom Hewitson, Founder and CEO, Labworks.io, joins us to share how he built a business on Alexa and Google Assistant, how he finds, keeps hold and monetises users, design best practice and advice for those looking to do the same.In 2017 and 2018, when Amazon Alexa began rolling our in-skill purchasing (ISP), many thought that there'd be a gold rush on the Alexa platform. Business will be built, money will be made and all will be well. It happened with the App Store on mobile, after all.There was two problem that most developers were facing: how do you create something that's good enough to keep users coming back for more, and then how do you create an offer for those users that's worth paying for?Those challenges turned out to be pretty difficult to overcome and, to date, only three companies have managed to reach the levels of success many were aiming for in the Alexa space: Matchbox, with their suite of quizzes and kids games, Invoked apps with it's load of sleep and ambient sounds and, our guest this week, Labworks, with Voice Arcade.One weekend, wanting to explore Alexa for investigatory purposes, in case any clients were to ask about it in future, Tom Hewiston, founder of then-chatbot agency, Labworks, set about building a game.After launching the game and pretty much forgetting about it, some months later, Tom received a call from Amazon. Turns out, Tom's game was the third most popular game on the Alexa platform. Amazon were starting to pay developers for having popular skills as an incentive for them to continue improving skills and developing new skills.These rewards were enough for Tom to employ someone to help build out more games. Labworks pivoted from building chatbots for clients and into building games for Alexa and the rest is history.We chat to Tom about his journey, what he's learned, his thoughts on the industry and advice for others looking to build successful skills and actions on Alexa and Google Assistant.Here's the running order:00:02:50 About Tom Hewitson and Labworks.io00:05:50 Last year's Alexa skills usage00:09:30 Was it good timing to launch Voice Arcade?00:11:15 Ten hot takes on voice: what's changed in voice since 2019?00:13:00 What's changed for the better?00:15:20 Developer rewards: how helpful were they?00:19:15 What works and what doesn't for in-skill purchasing?00:20:00 What's the difference in typical ISPs vs Voice Arcade?00:22:15 Challenges with ISPs, offering more value than you're asking for in return00:24:30 How are you showing value?00:26:00 Vishnu Saran: How are you solving discoverability?00:30:40 Marek Mis: Advice for hobbyist voice devs wanting to go pro?00:33:40 Is there much experimentation left?00:38:40 How do you prioritise and test features?00:40:55 Any new platform features you're excited about?00:43:00 Matt Buck: Have you thought about putting your games in apps or on web?00:47:09 Katy Boungard: Brand identity and sonic branding00:49:20 Richard Warzecha: Discovering features within skills00:50:00 How much time is spent on happy path vs everything else?00:55:44 Manual testing vs code testing00:57:05 Example of something that took a lot of iteration to get right00:58:35: Richard Warzecha: Transferable principles from games to other voice experiences01:03:00 Tooling and Jovo01:04:00 General takeaways and contact detailsLinksLabworks.ioFollow Tom Hewitson on TwitterJoin Tom Hewitson on LinkedInSay "Alexa, open Voice Arcade"Say "Hey Google, open Voice Arcade" See acast.com/privacy for privacy and opt-out information.
When it comes to making customer interactions with conversational AI more human-like, there's often one thing missing. Emotion.We chat to Nico Perony about how OTO.ai is being used to understand emotion and sentiment of users in order for businesses to create more compelling customer experiences.Married with conversational AI, bots can be more sensitive to the caller based on their emotional state and even do things like escalate calls to an agent based on an angry customer response.It's also being used to support agents in call centres to appraise tone and improve how agents speak with customers, as well as in gaming applications to detect abuse and toxicity and escalate occurrences to moderators.There is huge potential for this technology, not only in automating customer experience in a more human-like way, but also to gather insights from customer and staff voice relations and use it to improve the quality of service offered.We also continued this discussion on Clubhouse afterwards. Follow @kanesimms on Clubhouse for more open ended after show discussions.LinksVisit OTO.aiConnect with Nico on LinkedIn See acast.com/privacy for privacy and opt-out information.