Custom Voice Feature Can Help Brands Tweak IVR for Better Customer Experiences

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With the rise of digital assistants and conversational interfaces, people have grown accustomed to hearing and speaking to synthetic voices. But what do those voices sound like? Often, pretty repetitive. We’re all familiar with the Google Assistant voice, for example.
That’s why we are excited to announce the general availability of Custom Voice in our Cloud Text-to-Speech (TTS) API, a new feature that lets you train custom voice models with your own audio recordings to create unique experiences.
For businesses looking to build a strong brand identity, establishing a unique voice can help turn mobile app interactions or customer service based on interactive voice responses (IVR) into differentiated customer experiences. Our TTS API has included a speech synthesis service with a static list of voices for some time, but now, with Custom Voice, moving beyond these predefined options is easier than ever.
Custom Voice lets you simply submit your audio recordings to get access to the new voice directly in the TTS API. Custom Voice TTS includes guidance on the audio requirements to help make sure you generate a high quality custom TTS voice model. Once this new model is trained, all you have to do to start using the newly trained voice is reference the model ID in your calls to the Cloud TTS API.
At Google, we are committed to building safe and accountable AI products, not only because it’s the right thing to do, but because it is a critical step in ensuring successful use in production. As part of Google Cloud’s Responsible AI governance process, we conducted a deep ethical evaluation of Custom Voice TTS, and its relation to synthetic media, in order to surface and mitigate potential harms that it may create. If you are interested in Custom Voice TTS, there is a review process to help ensure each use case is aligned with our AI Principles and adequate voice actor consent is given.
Additionally, to verify that voice actors are actually the ones producing the audio, you will need to submit an audio file producing a sentence that Google Cloud chooses (for example: “I agree that my voice will be used to create a synthetic custom Text-to-Speech voice).
We’re looking forward to seeing this API help businesses solve problems in an easy, fast, and scalable way. TTS Custom Voice is now GA in these languages:
English (US)
English (AU)
English (UK)
Spanish (US)
Spanish (Spain)
French (France)
French (Canada)
Italian (Italy)
German (Germany)
Portugues (Brazil)
Japanese (Japan)
We plan to continue expanding this lineup in order to meet your needs. Ready to try for yourself? Contact your seller to get started on your use case evaluation today!
How the City of Memphis Uses Technology to Identify 75 Percent More Potholes

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At 340 square miles, the City of Memphis is among the largest in the United States in terms of land area. Memphis has over 6,800 lane-miles of city streets, enough to drive back and forth to Los Angeles four times. Keeping these streets well maintained and safe for citizens and visitors is a major priority for the city.
Lots of traffic, lots of roads, and a four-season climate prone to wintertime freeze-thaw-refreeze cycles means the opportunity for potholes. Although the city aims to fill potholes within five business days of notification, it can take longer, especially during winter and early spring. Last year, the city’s Public Works crews repaired some 63,000 potholes, only 20% of which were reported by residents. Approximately 32,000-man-hours each year are spent repairing potholes, with seasonal fluctuations requiring ten to twelve Street Maintenance crews working steadily during the winter months. Still, many went unreported, leading the city to flag pothole request resolution under “needs improvement” on its open data portal website.
Like many large cities, Memphis also struggles with vacant and blighted properties. Nearly 15,000 properties in Memphis are likely vacant, and city officials contend that many are owned by out-of-town investors who live elsewhere and do not take necessary restoration or maintenance steps. These properties can decrease the value of surrounding real estate and discourage new businesses and other residents from moving to an area. Citizen frustration and concerns over the number of blighted properties has made blight eradication a major focus of the City of Memphis.
Historically, residents reported potholes and blighted properties by calling 311, or more recently by using the Memphis 311 app. However, these reports only covered about 20 percent of the problems — often the worst cases. And by the time residents took the initiative to submit a 311 report, they usually weren’t feeling good about the situation.
Recognizing that potholes and vacant properties are often the most visible indicators of whether a city government is doing its job efficiently, Memphis Mayor Jim Strickland and CIO Mike Rodriguez began looking for ways they could apply technology to fix the problems. Mike approached Google for ideas, and Google recommended conducting a machine learning proof-of-concept (POC) with SpringML, a Google Cloud Partner.
“Memphis is focused on easy living, and we want to do everything we can to keep our citizens happy,” says Mike Rodriguez. “Working with Google and SpringML to reduce potholes and urban blight using machine learning and artificial intelligence was an easy decision.”
Bringing machine learning to city operations and budgets
The city’s goal is to detect potholes and abandoned properties by analyzing video footage of roads and residential properties. It wanted to classify potholes by width and depth, and share the information with workers who can repair them. For abandoned properties, it wanted to enable more strategic deployment of resources for homeowners citywide and take action to hold neglectful property owners accountable.
The POC began by training TensorFlow models for ML object detection using preconfigured AI Platform Deep Learning VM Images on Compute Engine. SpringML helped set up cameras and developed a user interface to collect pothole data and automate the 311 ticketing process.
Together, the teams analyzed 30 days of video from a moving city bus and high-resolution video from 360-degree cameras mounted to a code enforcement vehicle, overlaid with data from 311 reports. As the models were refined, accuracy quickly climbed from 50 percent to over 90 percent as models were taught to differentiate a pothole from a manhole cover or other object.
The city also imported routes, potholes, and paving data along with geolocation data from ArcGIS and Google Maps into BigQuery to better understand street conditions and the proximity of potholes to one another. BigQuery also analyzes city property records, tax records, 311 reports, and third-party survey data on-demand to predict where homes are starting to become run down and where neighborhood decay is most likely to occur. The SpringML team created a pilot analysis to begin vacant property protections and developed a user interface tool to interact with the model’s results.
“Google Cloud Platform made it possible for us to experiment with machine learning and artificial intelligence to help solve our city’s problems while working within the budget constraints of a municipal IT organization,” says Mike. “Google turned a ‘nice to have’ into a ‘let’s do this!'”
Identifying 75 percent more potholes
Memphis expects to substantially reduce the number of potholes on its streets, creating a better driving experience for residents and visitors alike. Because drivers won’t be as likely to swerve to miss a pothole, streets will be safer and friendlier to bicycles and scooters. Fewer potholes will also save the city between $10,000 and $20,000 annually in city claims that it pays out in cases where vehicle damage results from a pothole that was not addressed in a timely manner.
“Historically, Public Works has relied primarily upon Street Maintenance crews to proactively locate and fill potholes. As Memphis has over 6,800 lane-miles of public streets, it is a daunting task to reliably survey the entire system in an efficient and systematic way,” says Robert Knecht, Public Works Director for the City of Memphis. “The outcome of the data collected will be invaluable to Public Works so that it can ensure it is managing the city’s street system in a more proactive manner.”
Memphis will be able to better prioritize road maintenance based on condition and impact, increasing the efficiency of its Public Works road crews. Analyzing video of streets also gave the city visibility into issues it wasn’t previously aware of, such as curbs, gutters, and manhole covers that had been mistakenly paved over and need to be excavated. The ML process is easily transferrable to other concerns as well, helping the city identify illegal signs or spools of cable hanging on light posts that could be potentially unsafe.
Helping communities recover and thrive
Memphis is also having success in analyzing predictive trends to combat high rates of abandoned and blighted properties, surpassing 97.5 percent accuracy. “In the past, Public Works experimented with comprehensive, city-wide blight identification by using approximately 200 volunteers to survey and photograph over 237,000 city parcels. This effort was costly, took a long time to complete, and resulted in inconsistent data collection,” says Robert. “Blighted property conditions can change quickly in a city the size of Memphis. Now, with this new technology, Memphis will be able to make a significant difference in the efforts to proactively and comprehensively identify and manage blighted and substandard properties.”
Code Enforcement with better data-driven detection mechanisms enables the city to also identify cases where homeowners are not physically or financially able to keep up with the challenges of homeownership and make them aware of resources that are available to assist them. Memphis Code Enforcement can do a better job of finding people living in derelict properties that pose hazards to inhabitants’ health and safety, and help them fix those problems or find a new place to live.
“Using SpringML and Google Cloud Platform to detect indicators of vacant or blighted properties will help Memphis create safer neighborhoods that will be more attractive to businesses and home buyers,” says Mike. “Property values and employment will go up, crime will go down, and social services can be more focused and effective.”
Revolutionizing service delivery for citizens
Memphis is proving the viability of a cost-effective, cloud-based machine learning model that other cities can follow. The city is already looking into new applications of AI and ML that will further improve city services and help it build a better future for its 652,000 residents.
As part of his commitment to a transparent government, Memphis Mayor Jim Strickland created an open data policy that commits to releasing raw data and sharing it with citizens in a variety of downloadable formats. Going forward, this transparency will help citizens understand how their needs are being served and uncover new, innovative use cases for AI and ML.
“Our goal is to become a smart city, and technologies such as Google Cloud Platform and SpringML put us ahead of the game,” says Mayor Strickland. “Google understands data, and there isn’t a better company to help us analyze our data resources for actionable insights.”

AirAsia Turns to Google Cloud to refine Pricing, Increase Revenue, and Improve Customer Experience
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AirAsia needed a platform incorporating products that could capture, process, analyze, and report on data, while delivering value for money and meeting its speed and availability requirements. The airline also wanted to minimise infrastructure management and system administration demands on its technology team members.
The airline conducted a proof of concept and found Google Cloud Platform—including the Google BigQuery analytics data warehouse—was the best fit.
AirAsia was impressed by the ease and flexibility with which it could extract, transform, and load customer data from its systems, websites, and mobile applications into Google BigQuery for analysis. Reporting and dashboards were quickly and effectively delivered through Google Data Studio.
“With a minimal number of people involved, we can very quickly transform an idea or thought process into a deliverable. Prior to Google Cloud Platform, bringing those ideas to fruition would have been impossible,” says Nikunj Shanti, Chief Data and Digital Officer, AirAsia.
Google Cloud VMware Engine Achieves HIPAA Compliance

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We are excited to announce that as of April 1, 2021, Google Cloud VMware Engine is covered under the Google Cloud Business Associate Agreement (BAA), meaning it has achieved HIPAA compliance. Healthcare organizations can now migrate and run their HIPAA-compliant VMware workloads in a fully compatible VMware Cloud Verified stack running natively in Google Cloud with Google Cloud VMware Engine, without changes or re-architecture to tools, processes, or applications.
Healthcare organizations increasingly use cloud platforms to personalize patient care, analyze large datasets more effectively, enhance research and development collaboration, and share medical knowledge. Leveraging cloud platforms can also help healthcare organizations increase the privacy and security of information systems, including protected health information (PHI), and, as a result, better comply with applicable laws and regulations while reducing the burden of compliance. For PHI, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) set standards in the United States to protect individually identifiable health information. HIPAA applies to health plans, most healthcare providers, and healthcare clearinghouses that manage PHI electronically, and to persons or entities that perform certain functions on their behalf.
With Google Cloud, organizations can leverage solutions that enable secure, continuous patient care and data-driven clinical and operational decisions with ease, while being empowered with collaboration and productivity tools. Further, Google Cloud Platform supports HIPAA compliance. We offer HIPAA-regulated customers the same products at the same pricing that is available to all customers, unlike many other cloud providers.
For healthcare organizations that leverage VMware on-premises, having a consistent, cloud-integrated platform that provides seamless access to native cloud services unlocks the opportunity to extend, migrate, and modernize healthcare IT infrastructure and applications in a fast, low-risk manner at their own pace. This is especially important for mission-critical healthcare provider workloads, where having a low-risk way to adopt the cloud is important. Google Cloud VMware Engine offers that solution. By achieving coverage under Google Cloud’s BAA, Google Cloud VMware Engine enables healthcare organizations to realize the benefits of cloud computing and stay on track with their HIPAA compliance efforts without additional complexity. This is very relevant in hybrid scenarios, where customers would like to leverage other native cloud services such as analytics and big data processing, without having to enter into multiple BAAs.
Google Cloud VMware Engine offers dedicated, isolated software-defined datacenter environments with fully redundant and dedicated 100 Gbps networking that are suitable for healthcare organizations to run applications storing and processing PHI data. Customers have the ability to encrypt their virtual storage area network (vSAN) using an external key management server. Healthcare customers can run their workloads in a native VMware environment—vSphere, vCenter, vSAN, NSX-T, and HCX—while benefiting from Google Cloud’s highly performant infrastructure to meet the needs of their workloads. Customers can connect their VMware applications to native Google Cloud services such as BigQuery and artificial intelligence (AI) to derive new insights from existing data and quickly make informed decisions.
Protecting against and mitigating the impact of ransomware attacks is top-of-mind for Healthcare organizations. This requires building a cyber resilience program and back-up strategy to prepare for how users can restore core systems or assets affected by a security (in this case, ransomware) incident. This is a critical function for supporting recovery timelines and lessening the impact of a cyber event so organizations can get back to operating their business. Google Cloud VMware Engine in combination with Google Cloud first party solutions such as Actifio Go, or partner solutions such as NetApp CVO can provide an efficient way to recover incremental point-in-time backups along with on-demand provisioning of new compute to recover both data and infrastructure from Ransomware attacks quickly and efficiently.
Healthcare customers can also use Google Cloud VMware Engine as a disaster recovery (DR) target for their on-premises VMware workloads. Healthcare organizations also need a business continuity plan for their mission critical applications. When a disaster occurs, hospitals need their data protected so they can quickly get back to treating patients. It is a HIPAA requirement that healthcare organizations must be able to recover from a natural disaster. Google Cloud VMware Engine offers a like-for-like cost-effective DR target for these customers. The DR environment can be operated without new training using the same tools as their on-premises deployment. Google Cloud VMware Engine is currently available in 12 regions across the globe including three regions in the US, which means our regional and multi-national customers can take advantage of this service for geographic diversification as well.
If you are interested in understanding more and taking advantage of Google Cloud VMware Engine, contact your Google sales team now.
For details, see HIPAA compliance on Google Cloud Platform.
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Creating Value With the Breadth and Depth of AI Platform
Watch Craig Wiley, Director of Product Management – Google Cloud, as he breaks down and simplifies AI for enterprises and the adoption of AI.
“As I think about AI, fundamentally AI only does two things. One it helps you grow your market, increase subscribership, increase users, increase their spend or increase their conversion. Or it helps you in the back-end. It can drive efficiencies, reduce costs and drive out waste from the system.
He also talks about how customers have unlocked the power of data by utilizing Google’s AI Platform. From APIs to AutoML to writing your own model code, he will show real-world examples of how customers create value, and critical tips on how to accelerate your own AI journey.
Finally, he will show how can Google Cloud maps business strategy to the right AI absorption strategy and the different ways that Google Cloud can help you deploy AI without compromising flexibility speed, quality or scale.
AI-powered Business Messages for Timely, Engaging and Helpful Conversations with Customers

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Over the last two years, we’ve seen a significant uptick in the number of people using messaging to connect with businesses. Whether it was checking hours of operation, verifying what was in stock, or scheduling a pick-up, the pandemic caused a significant shift in consumer behavior.
- 45% of users are spending more time on messaging services because of the pandemic
- 85% of consumers would like to message brands directly
With the rise in demand for messaging, consumers expect communication with businesses to be speedy, simple, and convenient. For businesses, keeping up with customer inquiries can be a labor-intensive process, and offering 24/7 support outside of store hours can be costly.
To help businesses seamlessly deliver helpful, timely, and engaging conversations with customers when and where they need help, we introduced AI-powered Business Messages.
https://youtube.com/watch?v=fcgP3RHjBLY%3Fenablejsapi%3D1%26
What is AI-powered Business Messages?
With AI-powered Business Messages, you can connect with your customers in their moment of need, in the places they’re looking for answers—such as Google Search, Google Maps, or any brand-owned channel. For instance, check out how Walmart customers in the US are able to receive real-time information on product availability, straight from a search results page.

People turn to Google when they are searching for answers to their questions, looking to buy something, or trying to accomplish a particular task with one of our many tools. In fact, 68% of all online experiences begin with a search engine.
At Google, we know how important it is for interactions with a brand to be personalized, helpful, and simple. With AI-powered Business Messages, customers are able to chat with virtual agents that understand, interact, and respond in natural ways.
We are also combining smart automation with the ability for customers to chat with live agents when it’s really needed. This approach saves your customers precious time, while also saving you money. And with Business Messages automatically handling many customer inquiries in the background, businesses have the option to distribute their human customer service agents to address other needs.
Getting started with conversational AI is easy with Bot-in-a-Box
We know it can be difficult to get started with AI. That’s why we are utilizing existing Google AI tools like Dialogflow—part of Google Cloud Contact Center AI—to create the capability within Google’s Business Messages called Bot-in-a-Box, which makes getting started with Conversational AI easy. Bot-in-a-Box allows for fast and effective adoption of automation for businesses of all sizes.
Enabling Business Messages with Bot-in-a-Box can be as simple as leveraging an existing customer FAQ document you already have, whether it’s from a web page or an internal document. And since the conversational AI is powered by Business Messages and Dialogflow working together, your chat bot is able to understand and respond to customer questions automatically without the need to write code.
Bot-in-a-Box also supports other critical journeys like “Custom Intents.” That means that your bot is able to understand the different ways customers express a similar question and respond accurately by using machine learning capabilities.

Finding success
In April 2021, Wake County courthouses in North Carolina partnered with Tango Technology to implement Business Messages when it became apparent that being able to provide the public and attorneys with around-the-clock access to information would significantly reduce the pressure on courthouse staff. Using Bot-in-a-Box, Tango Technology was able to customize a solution for Wake County Courthouse, Justice Center, and Clerk of Superior Court in just four days.
“With the combination of Google’s Business Messages, GCP, and Dialogflow, we were able to spin up an AI-driven bot for the courts in days. And the technology stack allows us to continually improve by adding functionality in an agile process.”— Mike Lotz, Co-Founder, Tango Technology

With Business Messages, North Carolina courthouses saw a 37% decrease in the call volume handled by courthouse staff. With 398,298 fewer phone calls during the first year of operation, the AI-based messages helped Wake County Courthouse work more efficiently and productively.
We’ve seen many brands benefiting from AI-powered Business Messages. For instance, Levi’s saw a 30% increase in off-hours shoppers and surpassed 85% customer satisfaction scores after implementing Business Messages. They also drove 30x more store-related questions than Levi’s website chat.
Bring Google’s conversational AI to your storefront with Business Messages
Google’s Business Messages makes it easier for businesses of all sizes to engage their existing or potential customers in a virtual conversation, when and where they need it.
To learn more, watch our Cloud Next session here or visit us at g.co/businessmessages. We have specialized services to help you get started and can share the wisdom of our channel partners and dedicated experts who specialize in unleashing the potential of conversational AI.
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