A user initiates the call and selects the source language, such as Spanish. (In this example, assume that the target language is set to English.) As the user is talking to the support representative, the audio is converted to text using the Speech to Text service. Then using Language Translator, the text is translated to English. English language text is then sent to the Text to Speech service as input. The output audio message is what the support representative hears. All of this happens in near real time. The text from Speech to Text and the Language Translator service also can be stored in a database for analytics. The same process is repeated in reverse for the audio message sent by support personnel.

Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.

Glossary:Terms You Should Know Take your data analysis and deep learning expertise to the next level with these industry terms.

It is imperative that organizations start looking now for smarter solutions to the problems associated with unstructured data. There are many issues related to unstructured data that need to be readily addressed such as storage, discovery, organization, tagging and deduplication. One of the most important issues related to unstructured data is finding and discovering key business insights as quickly as possible, preferably in near real time, to gain a significant competitive advantage.

AlchemyAPI’s approach to natural language processing incorporates both linguistic and statistical analysis techniques into a single unified system. This hybrid approach provides an industry-leading advantage since both techniques have benefits and drawbacks depending on the content and specific usecases. Linguistic analysis takes a basic grammatical approach to understand how words combine into phrases, and how those phrases combine into sentences. While this approach works well with editorialized text (e.g., news articles and press releases), it does not perform as well when it comes to usergenerated content, often filled with slang, misspellings and idioms. Statistical analysis, however, understands language from a mathematical standpoint and works well on “noisy” content (e.g., tweets, blog posts, and Facebook status updates). The combination of these two approaches allows for increased accuracy on a variety of content.

Powered by IBM i Solution Editions hardware, IBS's ERP applications enable improved efficiencies, scalability and cost savings.

Former Intel CEO Andy Grove once coined the phrase, “Technology happens.” As true as Grove’s pat aphorism has become, it’s not always good news. Twenty years ago, no one ever got fired for buying IBM. In the heyday of customer relationship management (CRM), companies bought first and asked questions later. Nowadays, executives are being enlightened by the promise of big data technologies and the role data plays in the fact-based enterprise. Leaders in business and IT alike are waking up to the reality that – despite the hype around platforms and processing speeds – their companies have failed to established sustained processes and skills around data.

In a recent report, Aberdeen's research suggests that Hadoop usage could be a catalyst for an enhanced and well-rounded data strategy. Read on to find out more.

Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.

This Knowledge Brief investigates the impact of a data lake maintained in a cloud or hybrid infrastructure.

This document outlines how Best-in-Class firms use efficient content processes to achieve higher levels of customer centricity.

The purpose of this executive brief is to explore the challenges companies face in implementing enterprise search and to offer a new, robust set of technologies to help.

IT departments are under constant pressure to deliver improved user experiences that lead to revenue growth. Achieving this goal requires addressing multiple areas at once: taking advantage of the flexibility and scalability of the cloud; empowering mobile users with anytime, anywhere access; and accelerating digital transformation.

Are you making the most of your enterprise content? Doing so can mark the difference between being a disruptor and being disrupted. Download this infographic to find out more.

The number 1 independent tire retailer tried, unsuccessfully, to build an online platform based on Windows. Ultimately, the company succeeded instead with a solution built with Red Hat Enterprise Linux, Red Hat Network Satellite, Apache, WebLogic, and IBM Lotus Domino Server.

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Take a look at this summary which reveals that companies who have implemented comprehensive B2B Integration programs are reaping huge benefits!

Need for Speed and Flexibility Drives Manufacturers to Reengineer External Processes Around B2B Integration.

The 2017 CEI results indicate that brands have significant room for improvement in terms of satisfying customer expectations: On a scale from 0 to 100, the average CEI score is 33. Download this white paper to find out more.

This Total Economic Impact (TEI) analysis has been prepared exclusively for you based on your inputs. The analysis provides a high-level estimate of the impact of implementing IBM customer behavior analytics solutions.

Read this white paper to discover the 5 best practices for understanding customer journeys.

The analytics tools you’ve come to rely on probably haven’t kept pace with this rapid change, and may now be less effective. Systems may not be nimble enough to follow customer journeys across channels and time. Different platforms in different departments can’t talk to each other, so reporting is slowed. And it’s difficult to take proactive steps when your view of the total customer experience is a little blurry. Download this white paper to find out more.

SugarCRM has leveraged IBM and other strategic partnerships to broaden its omnichannel appeal to enterprises, making Sugar a strong alternative to Salesforce.com, Microsoft, Oracle and SAP. Learn how SugarCRM's four-pillar strategy enables businesses to create extraordinary customer experiences.

According to industry analyst IDC, the mean cost of an hour of downtime can range from USD 224,952 to USD 1,659,428, depending on the size of your organization.1 And each instance of downtime increases your total cost of ownership (TCO) and eats away at your IT budget.