Speech Synthesis Markup Language: An Introduction
Speech Synthesis Markup Language Specification (SSML 1.0), introduced in September 2004, is one of the standards enabling access to the Web using spoken interaction. It's designed to provide a rich, XML-based markup language for assisting the generation of synthetic speech in web and other applications. The essential role of SSML is to provide authors of synthesizable content a standard way to control aspects of speech such as pronunciation, volume, pitch, rate, etc., across different synthesis-capable platforms.
The SSML specification is based upon JSML and JSGF specifications, which are owned by Sun. Originally JSML (JSpeech Markup Language) was developed as a very simple XML format used by applications to annotate text input to speech synthesizers. JSML had characteristics very similar to SSML: it defined elements that described the structure of a document, provided pronunciations of words and phrases, indicated phrasing, emphasis, pitch and speaking rate, and controlled other important speech characteristics. The letter "J" in the markup language name has come from the Java(TM) Speech API, introduced by Sun in collaboration with leading speech technology companies, for incorporating speech technology into user interfaces of applets and applications based on Java technology. The design of JSML elements and its semantics are quite simple. Here is the typical self-explaining example:
<jsml> <voice gender="female" age="20"> <div type="paragraph"> You have an incoming message from <emphasis>Peter Mikhalenko</emphasis> in your mailbox. Mail arrived at <sayas class="time">7am</sayas> today. </div> </voice> <voice gender="male" age="30"> <div type="paragraph"> Hi, Steve! <break/> Hope you're OK. </div> <div> Sincerely yours, Peter. </div> </voice> </jsml>
The JSpeech Grammar Format (JSGF) is a representation of grammars for use in speech recognition. It defines a platform- and vendor-independent way to describe one type of grammar, a rule grammar (also known as a command and control grammar or regular grammar). Grammars are used by speech recognizers to determine what the recognizer should listen for and so describe the utterances a user may say. JSGF is not an XML format and is out of scope of this article.
SSML's Place in the Global Scope
Voice browsers are a very important part of Multimodal Interaction and Device Independence, making web applications accessible with multiple modes of interaction. A voice browser is a device that interprets a markup language and is capable of generating voice output or interpreting voice input, and possibly other input/output modalities. There is a whole set of markup specifications for voice browsers developed at W3C, and SSML is a part of it. Speech synthesis is a process of automatic generation of speech output from data input which may include plain text, marked up text or binary objects. It must be practical to generate speech synthesis output from a wide range of existing document representations. The common requirement to speech synthesis markup is that speech output from HTML, HTML with CSS, XHTML, XML with XSL, and DOM must be possible. The intended use of SSML is to improve the quality of synthesized content.
The key concepts of SSML are
- interoperability, or interacting with other markup languages (VoiceXML, SMIL etc.);
- consistency, or providing predictable control of voice output across platforms and across speech synthesis implementations; and
- internationalization, or enabling speech output in a large number of languages within or across documents.
The system of automatic generation of speech output from text or annotated text input that supports SSML must render a document as spoken output using the information contained in the markup to render the document as intended by the author. There are several steps in a speech synthesis process.
- XML parse. The incoming text document is parsed and the document tree with content are extracted.
- Structure analysis. The structure of a document influences the way in which a document should be read. For example, there are common speaking patterns associated with paragraphs and sentences.
- Text normalization. All written languages have special
constructs that require a conversion of the written form (orthographic
form) into the spoken form. Text normalization is an automated process
of the synthesis processor that performs this conversion. For example,
for English, when "$1000" appears in a document it may be spoken as
"one thousand dollars." The orthographic form "1/2" may be
potentially spoken as "one half," "January second," "February first,"
"one of two," and so on. By the end of this step the text to be spoken
has been converted completely into tokens. The exact details of what
constitutes a token are language-specific. A
<say-as/>element can be used in the input document to explicitly indicate the presence and type of these constructs and to resolve ambiguities.
- Text-to-phoneme conversion. After the processor has
determined the set of words to be spoken, it must derive
pronunciations for each word. Word pronunciations may be conveniently
described as sequences of phonemes, which are units of sound in a
language that serve to distinguish one word from another. Each
language has a specific phoneme set. This step is quite hard and
complex according to several reasons. First of all, there are
differences between written and spoken forms of a language, and these
differences can lead to indeterminacy or ambiguity in the
pronunciation of written words. For example, in English, "read" may be
spoken as "reed" (I will read the book) or "red" (I have read the
book). Both human speakers and synthesis processors can pronounce
these words correctly in context but may have difficulty without
<phoneme/>element of SSML allows a phonemic sequence to be provided for any word or word sequence.
- Prosody analysis. Prosody is the set of features of
speech output that includes the pitch (also called intonation or
melody), the timing (or rhythm), the pausing, the speaking rate, the
emphasis on words and many other features. Producing humanlike
prosody is important for making speech sound natural and for correctly
conveying the meaning of spoken language. In SMIL there are special
<prosody/>for prosody purposes, which I will describe below.
- Waveform production. This is a final step in producing
audio waveform output from the phonemes and prosodic
information. There are many approaches to this processing step so
there may be considerable processor-specific
<voice/>element in SSML allows the document creator to request a particular voice or specific voice qualities (e.g. a young male voice).
SSML provides a standard way to specify gross properties of synthetic speech production such as pronunciation, volume, pitch, rate, etc. Exact specification of synthetic speech output behavior across disparate processors, however, is beyond the scope of the SSML specification. It should be noticed that markup values are merely indications rather than absolutes. For example, it is possible for an author to explicitly indicate the duration of a text segment and also indicate an explicit duration for a subset of that text segment. If the two durations result in a text segment that the synthesis processor cannot reasonably render, the processor is permitted to modify the durations as needed to render the text segment.
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