1. Field of the Invention
The field of the invention is data processing, or, more specifically, methods, systems, and products for supplementing audio recorded in a media file.
2. Description of Related Art
Managers are increasingly isolated from one another and their employees. One reason for this isolation is that managers are often time constrained and their communication occurs with many different devices and often communications requires two or more managers or employees to be available at the same time. There therefore is a need for improvement in communications among users such as managers and employees that reduces the devices used to communicate and reduces the requirement for more than one user to communicate at the same time.
Methods, systems, and computer program products are provided for supplementing audio recorded in a media file. Embodiments include receiving a media file; identifying the subject matter of audio portion of the media file; identifying supplemental content for supplementing the subject matter recorded in the audio portion of the media file; and inserting in the media file markup for rendering the supplemental content.
The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular descriptions of exemplary embodiments of the invention as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts of exemplary embodiments of the invention.
Exemplary methods, systems, and products for asynchronous communications and supplementing audio recorded in a media file according to the present invention are described with reference to the accompanying drawings, beginning with
The system of
The example of
The library management system (104) of
The exemplary system of
The exemplary system of
The exemplary system of
The exemplary system of
The handheld recording devices (108 and 114) of
The arrangement of devices making up the exemplary system illustrated in
Asynchronous communications in accordance with the present invention is generally implemented with computers, that is, with automated computing machinery. In the system of
Stored in RAM (168) is a library management application (202) for asynchronous communications according to the present invention including computer program instructions for receiving a recorded message, the message recorded on a handheld device; converting the recorded message to text; identifying a recipient of the message in dependence upon the text; associating the message with content under management by a library management system in dependence upon the text; and storing the message for transmission to another handheld device for the recipient.
The library management application (202) of
The library management application (202) of
The library management application (202) of
The library management application (202) of
Also stored in RAM (168) is an application server (155), a software platform that provides services and infrastructure required to develop and deploy business logic necessary to provide web clients with access to enterprise information systems. Also stored in RAM (168) is an operating system (154). Operating systems useful in computers according to embodiments of the present invention include UNIX™, Linux™, Microsoft XP™, AIX™, IBM's i5/OS™, and others as will occur to those of skill in the art. Operating system (154) and library management module (202) in the example of
Library management system (104) of
The exemplary library management system of
The exemplary library management system (104) of
For further explanation,
The method of
The method of
The method of
To accommodate larger vocabularies, speech recognition engines use language models or artificial grammars to restrict the combination of words and increase accuracy. The simplest language model can be specified as a finite-state network, where the permissible words following each word are explicitly given. More general language models approximating natural language are specified in terms of a context-sensitive grammar.
Examples of commercial speech recognition engines currently available include SpeechWorks available from Nuance Communications, Dragon NaturallySpeaking also available from Nuance Communications, ViaVoice available from IBM®, Speech Magic available from Philips Speech Recognition Systems, iListen from MacSpeech, Inc., and others as will occur to those of skill in the art.
The method of
The method of
The method of
The method of
To aid users in communication, content identified as associated with communications among users may be identified, described in speech, and presented to those users thereby seamlessly supplementing the existing communications among the users. For further explanation,
Typically, speech synthesis engines operate by using one or more of the following categories of speech synthesis: articulatory synthesis, formant synthesis, and concatenative synthesis. Articulatory synthesis uses computational biomechanical models of speech production, such as models for the glottis and the moving vocal tract. Typically, an articulatory synthesizer is controlled by simulated representations of muscle actions of the human articulators, such as the tongue, the lips, and the glottis. Computational biomechanical models of speech production solve time-dependent, 3-dimensional differential equations to compute the synthetic speech output. Typically, articulatory synthesis has very high computational requirements, and has lower results in terms of natural-sounding fluent speech than the other two methods discussed below.
Formant synthesis uses a set of rules for controlling a highly simplified source-filter model that assumes that the glottal source is completely independent from a filter which represents the vocal tract. The filter that represents the vocal tract is determined by control parameters such as formant frequencies and bandwidths. Each formant is associated with a particular resonance, or peak in the filter characteristic, of the vocal tract. The glottal source generates either stylized glottal pulses for periodic sounds and generates noise for aspiration. Formant synthesis often generates highly intelligible, but not completely natural sounding speech. However, formant synthesis typically has a low memory footprint and only moderate computational requirements.
Concatenative synthesis uses actual snippets of recorded speech that are cut from recordings and stored in an inventory or voice database, either as waveforms or as encoded speech. These snippets make up the elementary speech segments such as, for example, phones and diphones. Phones are composed of a vowel or a consonant, whereas diphones are composed of phone-to-phone transitions that encompass the second half of one phone plus the first half of the next phone. Some concatenative synthesizers use so-called demi-syllables, in effect applying the diphone method to the time scale of syllables. Concatenative synthesis then strings together, or concatenates, elementary speech segments selected from the voice database, and, after optional decoding, outputs the resulting speech signal. Because concatenative systems use snippets of recorded speech, they often have the highest potential for sounding like natural speech, but concatenative systems typically require large amounts of database storage for the voice database.
The method of
As discussed above, associated messages with content under management often requires identifying the content. For further explanation,
The method of
In some cases, the messages comprising communications among users may contain an explicit identification of content under management. For further explanation,
As mentioned above, the content of messages stored in audio portion of media files for asynchronous communications and other content stored in the audio portion of a media file may be supplemented to provide additional information and often added enjoyment for a user. For further explanation, therefore,
The exemplary media file of
The method of
Identifying (704) the subject matter of audio portion (712) of the media file (306) may be also carried out by converting the audio portion to text and determining a subject matter from the text. As discussed above, converting the audio portion to text may be carried out by a speech recognition engine such as, for example, SpeechWorks available from Nuance Communications, Dragon NaturallySpeaking also available from Nuance Communications, ViaVoice available from IBM®, Speech Magic available from Philips Speech Recognition Systems, iListen from MacSpeech, Inc., and others as will occur to those of skill in the art.
Determining a subject matter from the text may be carried out by parsing the text in dependence upon rules predetermined to identify words indicative of the subject matter of the content recorded on the audio portion of the media file. Such rules may for example ignore commonly used words such as ‘a,’ ‘the,’ ‘and’ and so on and then use a weighted algorithm to extract words that may be used to determine the subject matter of the content recorded on the audio portion of the media file.
The method of
The markup may include markup for visual rendering by a browser such as, for example, HyperText Markup Language (‘HTML’). The markup may also include voice markup to be rendered by a multimodal browser such as for example VoiceXML, X+V (‘XHTML plus Voice’) and so on as will occur to those of skill in the art.
The method of
Having included the markup for supplementing the content recorded in the audio portion of the media file, the markup may now be rendered to supplement in real time the audio played on a handheld recording device. For further explanation, therefore,
The method of
The method of
For improved user experience, the supplemental content may be rendered synchronized with the playback of the content on the media file. For example, the timing of content rendered according to the markup on the browser may be timed according to duration of the audio recorded on the media file. In some embodiments of the method of
Exemplary embodiments of the present invention are described largely in the context of a fully functional computer system for asynchronous communications using messages recorded on handheld devices and supplementing audio recorded in a media file. Readers of skill in the art will recognize, however, that the present invention also may be embodied in a computer program product disposed on computer readable media for use with any suitable data processing system. Such computer readable media may be transmission media or recordable media for machine-readable information, including magnetic media, optical media, or other suitable media. Examples of recordable media include magnetic disks in hard drives or diskettes, compact disks for optical drives, magnetic tape, and others as will occur to those of skill in the art. Examples of transmission media include telephone networks for voice communications and digital data communications networks such as, for example, Ethernets™ and networks that communicate with the Internet Protocol and the World Wide Web as well as wireless transmission media such as, for example, networks implemented according to the IEEE 802.11 family of specifications. Persons skilled in the art will immediately recognize that any computer system having suitable programming means will be capable of executing the steps of the method of the invention as embodied in a program product. Persons skilled in the art will recognize immediately that, although some of the exemplary embodiments described in this specification are oriented to software installed and executing on computer hardware, nevertheless, alternative embodiments implemented as firmware or as hardware are well within the scope of the present invention.
It will be understood from the foregoing description that modifications and changes may be made in various embodiments of the present invention without departing from its true spirit. The descriptions in this specification are for purposes of illustration only and are not to be construed in a limiting sense. The scope of the present invention is limited only by the language of the following claims.
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20080162131 | Bodin | Jul 2008 | A1 |
20080162559 | Bodin | Jul 2008 | A1 |
20080275893 | Bodin et al. | Nov 2008 | A1 |
20090271178 | Bodin | Oct 2009 | A1 |
20100223223 | Sandler et al. | Sep 2010 | A1 |
Number | Date | Country |
---|---|---|
1123075 | May 1996 | CN |
1298173 | Jun 2001 | CN |
1368719 | Sep 2002 | CN |
1197884 | Apr 2002 | EP |
236995 | Dec 2002 | GB |
20010071517 | Jul 2001 | KR |
20040078888 | Sep 2004 | KR |
WO 0182139 | Nov 2001 | WO |
WO 2005106846 | Nov 2005 | WO |
Entry |
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U.S. Appl. No. 11/266,662 Final Office Action mailed Oct. 30, 2008. |
U.S. Appl. No. 11/266,675 Final Office Action mailed Apr. 6, 2009. |
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Number | Date | Country | |
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20080161948 A1 | Jul 2008 | US |