Enhancing Authentic Language Learning Experiences through Internet Technology. ERIC Digest.

by LeLoup, Jean W. – Ponterio, Robert

With the focus on language, communication, and culture in the national standards for foreign language learning (Standards, 1999), foreign language teachers are continually searching for better ways of accessing authentic materials and providing experiences that will improve their students’ knowledge and skills in these target areas. As the Internet has transformed communication around the world, it is natural that it should play a major role in the foreign language classroom.

The instant worldwide connections enabled through the Internet have changed the way people everywhere think about communication, information, and doing business. Although Internet applications are really just computer programs that know how to use the Internet to interact, we view them as an extension of the world that we live in, an extension that brings the world to our fingertips. We can share all sorts of things with the world, get authentic materials from anywhere, and interact with people in distant locations as never before. How can Internet software enhance the classroom experience? In addition to the original Internet applications, like FTP for moving files between machines and Telnet for logging into distant computers, the wide range of features and media (text, image, sound, video, multimedia) supported by the current crop of Internet programs makes them powerful additions to the foreign language teacher’s repertoire. This digest highlights a number of Internet applications that can be used to enrich the foreign language classroom.

ELECTRONIC MAIL

Email was in use before the Internet as we know it today even existed and is still the most commonly used Internet application. Foreign language teachers can integrate email-based activities into their curriculum (LeLoup, 1997; Warschauer, 1995). For example, international keypal projects that enable students to correspond with native speakers of the target language are easily implemented where participants have the necessary access, equipment, and foreign contacts (Knight, 1994; Shelley, 1996). The infrastructure requirements for email are minimal, making it the most available of all Internet tools. Distance learning is another curricular area where email is being used (Ponterio, 1996). Today’s email software can handle text in a wide variety of languages, can transmit diacritics, and can include word processed files as attachments. The software also allows us send sound and images as attachments that enhance the context of the written communication.

ELECTRONIC LISTS

Electronic discussion groups or “lists” (sometimes referred to as “LISTSERVs”) use email to provide a forum where people of similar interests can participate in a professional dialog and share resources. Hundreds of lists of interest to language teachers are available on the Internet. (See, for example, http://alabanza.com/kabacoff/Inter-Links/listserv.html to search for scholarly electronic lists.) Some are service lists, such as LLTI (Language Learning Technology International Discussion Forum), which distributes information about all aspects of the technology used in language teaching; and IECC (Intercultural E-Mail Classroom Connections, K-12), which provides a service for teachers seeking partner classrooms for international and cross-cultural electronic mail exchanges. Others are language specific and address topics as specific and diverse as their membership warrants (e.g., AATG, ESPAN-L, TESL-L). FLTEACH (Foreign Language Teaching Forum) is a list that cuts across language lines to discuss methodology, instructional innovation, professional articulation, and enhanced student learning, among other topics. Participation in electronic discussion lists can be a useful tool for professional development, particularly for educators who are isolated geographically or within their districts from other teachers of the same language (LeLoup & Ponterio, 1995a, 1995b).

When participating in discussions, certain rules and protocols (netiquette) should be observed. Following list guidelines and learning how to accurately express and gauge the tenor of a post or response (often by using smiley faces) are very important skills in this faceless communications environment. In addition, some lists are very active, and keeping up with the messages may be a daunting job. Most e-mail software can easily sort mail into separate folders to help manage list messages.

ELECTRONIC JOURNALS

Several electronic journals target foreign language professionals. Generally, these journals are free, are published on a regular basis, and do not exist in paper form. There are a number of reasons for publishing a journal online. First, electronic journals can reach a large and diverse audience in a timely manner and without the printing costs of a paper journal. Second, the hypermedia nature of Web-based journals enables articles to include links to related background or reference information located elsewhere on the Web. Third, a number of these journals have a technology focus, and electronic dissemination illustrates many of the technologies treated in a given issue. With good submission policies and a strong editorial board, an online journal can be as dependable as a similarly run traditional journal. Of particular interest are “Language Learning & Technology (LL&T)” (http://llt.msu.edu/) and “Teaching English as a Second Language: An Electronic Journal (TESL-EJ)” (http://www-writing.berkeley.edu/TESL-EJ/).

WORLD WIDE WEB

The Web browser, usually Netscape or Internet Explorer, is the window through which most people view the Internet. Thanks to its flexibility and integration of other services, the Web represents the broadest and most powerful Internet application, pulling many others in under its umbrella. It has two main defining elements. The hypertext link allows anything on one page to link to any other page in the world, and the ability to combine objects of many different types makes the Web page an excellent format for mixed media. The multimedia nature of the Web and the use of the Web page as an interface to other services have greatly expanded the power of the Internet by making it possible to display information using a combination of formats (Fidelman, 1996). This is essential for the delivery of authentic materials, including texts; images; sound recordings; video clips; virtual reality worlds; and dynamic, interactive presentations. For some media formats, additional helper applications or plug-ins must be downloaded and installed to enhance the Web browser. In addition, sophisticated programming functions, such as CGI, JavaScript, and Dynamic HTML can turn a Web page into an interactive computer program. All this can allow the student to work in interesting ways with the authentic materials found on the page.

STREAMING AUDIO AND VIDEO

One way of connecting students with native speakers and authentic A-V materials is by using the technologies of streaming audio and video, which virtually transport the target language environment to the second language classroom without waiting for huge files to download. Students can listen to live radio stations from around the world or hear pre-recorded broadcasts of music, news, sports, and weather. They may watch the nightly news from France or live TV from Chile transmitted to their computer in real-time. One of the many places to find online media of this sort is Media Info (http://emedia1.mediainfo.com/emedia/). This technology keeps getting better thanks to faster computers and better Internet connections. RealPlayer and Media Player are the two most common streaming formats, and both can be freely downloaded.

SEARCH ENGINES

The Web is so extensive that good tools are needed to help us find authentic materials that correspond to the topics of the foreign language curriculum. A search engine is an online “private eye” that does this detective work for the user. Search engines use keywords to find any site (documents, files, Web pages) that contains the keywords entered by the user. Some even calculate how good the match is so the most likely hits are presented first. The Web is growing and changing so fast that trying to navigate it and locate desired information without search engines would be a formidable task.
The Web has numerous search engines (e.g., Yahoo, Altavista, Google). Each one searches the Internet, creating extensive indexes of all of the words that it finds on all pages in all languages. When it finds links, the search engine examines those pages as well. Although there are language specific engines (e.g., Ole, Encuentrelo, Crawler.de Suche, Il ragno italiano, LOKACE, ECILA, SAPO), all of these tools work well for many languages. Each one performs a little differently, so it is a good idea to read the “help” page to learn the best techniques for doing simple and advanced searches with the engine you are using. In addition to searches, many of them also provide ready-made collections of pages on specific topics from current events to cooking to business.

REMOTE ACCESS TO LIBRARIES AND DATABASES

Many library catalogs, bibliographic resources, and other types of databases are available on the Internet through a Web browser. Many of these used to be housed in closed systems or on CDs, but more and more are now Internet accessible. The ERIC database is an example of an important resource available via the Web (http://www.accesseric.org/searchdb/searchdb.html), making it easy for teachers to locate Digests, Minibibs, and articles of interest on-line. The Perseus Project (http://www.perseus.tufts.edu/) includes an online database of classical texts. There are also databases of lesson plans and teaching resources, like RETANET (http://ladb.unm.edu/retanet/) for Latin America.

CHAT, AUDIO AND VIDEO CONFERENCING, MESSAGING

While much of the Internet is about the presentation of information, instant communication with other individuals allows an interpersonal exchange with a friend around the corner or around the world. Such real-time communication takes place via several different types of chat, conferencing, and messaging programs. One such application is Internet Relay Chat (IRC), which enables synchronous “conversation” among participants anywhere in the world. Users enter a channel and “talk” by typing messages to all of the other people on that channel; everything that is typed is seen instantly by everyone. Hundreds of channels exist, with names usually reflecting the topics and language discussed. Private closed channels can also be created for use in the classroom.

Audio and video conferencing programs, such as CUSeeMe and MS NetMeeting, are options for engaging foreign language students in voice conversation. Users can talk directly to their interlocutor and, using the proper hardware and software, can even see and be seen by the person they are addressing. These applications take a large amount of bandwidth and depend on a good modem connection; network traffic will also affect the results. The development and availability of broadband service through cable-modem and Digital Subscriber Line (DSL), which are much faster than modem access, is making desktop video conferencing a reality for an ever growing number of people.

Messaging software such as ICQ or Instant Messenger provides an instant connection to the people on a user’s list of contacts by letting the user know when those people are online. These programs facilitate quick communication by making a connection to an individual as easy as clicking on a name. These new technologies are already powerful and have the potential for tremendous impact on the ability of students to communicate directly with native speakers in target language environments.

WEB COURSE MANAGEMENT

Web course management software is designed for creating and managing online courses but can also be used to support and extend a traditional class by making materials with teacher annotation, glossaries, syllabus, and assignments available to the students through the Web. The collaboration tools built into this software for communicating with and among students have been exploited by language teachers for interactive homework by having students exchange messages in the target language in a real-time chat session or on a closed bulletin board (open only to the students in the class). The computer automatically saves these messages for the teacher. Two examples of course management software are WebCT and Blackboard.

CONCLUSION

Ultimately, it is incumbent upon the foreign languageteacher to integrate these tools into the curriculum in apedagogically sound and meaningful way. Clearly, targetlanguage communication and cultures are easily accessiblethrough current and emerging technologies, and informationabout using these resources is readily available online. Theintrepid and creative teacher will venture into this virtualrealm, find authentic resources, and use them to make thesecond language classroom a marvelous place to learn.

REFERENCES

Fidelman, C. G. (1996). A language professional’s guide to the World Wide Web. “CALICO Journal, 13″ (2 & 3); http://agoralang.com/calico/webarticle.html

Knight, S. (1994). Making authentic cultural and linguistic connections. “Hispania, 77,” 289-294.

LeLoup, J. W. (1997). But I only have e-mail–What can I do? “Learning Languages, 2,” 10-15.

LeLoup, J. W., & Ponterio, R. (1995a). Networking with foreign language colleagues: Professional development on the Internet. “Northeast Conference Newsletter, 37,” 6-10.

LeLoup, J. W., & Ponterio, R. (1995b). FLTEACH: Online professional dialogue. In M. Warschauer (Ed.), “Virtual connections: Online activities & projects for networking language learners” (pp.375-392). Honolulu, HI: University of Hawaii Press.

Ponterio, R. (1996). Internet resources for a French civilization course at SUNY Cortland: A pilot project. “NYSAFLT Annual Meeting Series, 11,” 43-50.

Shelley, J. O. (1996). Minneapolis and Brittany: Children bridge geographical and social differences through technology. “Learning Languages, 2,” 3-11.

“Standards for foreign language learning in the 21st century.” (1999). Lawrence, KS: Allen Press.

Warschauer, M. (Ed.) (1995). “Virtual connections: Online activities & projects for networking Language Learners.” Honolulu, HI: University of Hawaii Press

This article taken from: http://adilajefiza.wordpress.com/

An Analysis of the Phonology of Computer-Generated English Using the Festival Speech Synthesis System

Crystal Darby
LALS 3002
December 18, 2009
1 Introduction
The goal of computer-generated speech is to mimic natural language. Many scholars have
researched methods of creating synthesized voice to mimic the natural human voice. One
such effort is the open-source initiative, the Festival Speech Synthesis System (henceforth
just ‘Festival’).
This paper will begin by establishing the theoretical background concerning the phonological
phenomena that will be tested in Festival. Next, it will show the methodologies that
were used in order to gather data from Festival. Next, the results will be shown. I will
discuss the findings and expand on any interesting data that has resulted. Finally, I will
conclude with suggestions for the improvement of Festival as a speech synthesizer to ensure
high-quality and natural-sounding computer-generated English.
This paper makes contrasts between computer-generated English and theoretical phonological
rules of English. This paper does not contrast computer-generated English with a
native-speaking human participant on the argument that there are too many nuances concerning
dialectical variation and variation within speakers themselves. Also, Festival has a
good, but limited, choice of voices for comparison. I do not think it is very accurate to
compare the limited choices RP British English or American English that Festival provides
with the available Canadian English from a human participant. Nevertheless, this paper
attempts to uncover some of the theoretical models of English that Festival makes use of in
its program. The main research questions are:
1. Can Festival create human-like speech?
2. What kinds of phonological rules can we find evidence of being used in Festival?
3. Can Festival implement some allophonic variation rules for English?
This paper will attempt to answer these questions by focusing on some of the key areas
discussed in LALS 3002, Phonology I: features, morphophonemic analysis, phonological alternation,
syllables, stress, and intonation (Hayes, 2009). More specifically, this paper will
1
implement a wug test (Berko, 1958) for testing the phonological rules for pluralization to
answer the overall question: can festival create human-like speech?
2 Theoretical Background
The following theories have been established in the field of phonology (Hayes, 2009; O’Grady
& Archibald, 2004; Odden, 2005). This study makes use of the literature that exists on
English phonology and borrows and expands on the methods and procedures outlined in
this section (Berko, 1958; Labov, 1966).
2.1 Computer-generated Language
Computer-generated speech has often been criticized for its “hollow” or “tin can” sounding
voice, but many efforts have improved the quality of these voices. It does not seem unreasonable
to think that a computer can produce realistic sounding phonemes because phonemes
can be measured in waves. Waves can be easily modeled by computers. Of course, the
presence of a vocal tract is missing from a computer, but nevertheless, computers are able to
generate realistic-sounding phonemes in isolation because of their measurable quality. Phonetics
can be easily modeled, but what about phonology? We know that phonetics is the
study of sounds and phonology is the study of sound patterns. We have realized that the
phoneme /t/, for example, is not always realized as /t/ in natural speech. /t/ can become
a completely different phoneme in certain environments. The tapping rule for English is as
follows:
Rule 1. Tapping (adapted from Hayes (2009, p. 32) to use features)
26666664
- son
- approx
- voice
37777775
!
26666664
+ son
+ approx
+ voice
37777775
/ [+ syll]
2664
+ syll
- stress
3775
/t/ becomes /R/ when it is between a vowel and an unstressed vowel.
2
which allows us to generate the following output1:
butter attention
/b2t@~/ /@tEnS2n/ underlying forms
R – Rule 1. Tapping
[b2R@~] [@t˜EnS˜2n] surface forms
Even though we have “tt” orthographically in both “butter” and “attention,” it does
not necessarily mean it will correspond to /t/ in the phonology. One exhaustive way to
solve this problem without phonology would be to record all of the words in a language and
have the speech synthesizer access these recordings and arrange them into the order of the
given input. But, it would be inefficient to record and calculate all of the possible phonemic
alterations, especially since languages in general have a creative quality and can be generate
new combinations of words on the spot to create never before heard utterances. Recording
every word of a language would be nearly impossible! Therefore, a well-designed speech
synthesizer must make use of phonology to extract the correct output of the sounds of an
utterance. In the tapping case, it is not that bad if the synthesizer fails because /t/ and /R/
are not contrasts of one another. That is, /b2R@~/ and /b2t@~/ do not signal two different
words in English. They both correspond to the word “butter.” This may not be the case
in other languages. It is true of Spanish that /t/ and /R/ contrast (Hayes, 2009, p. 32).
Thus, it is particularly important that computer-generated speech can not only recognize
allophonic variation of one language but also realize the differences of other languages.
2.2 Wug Testing
Berko (1958) performed a simple experiment to test for a child’s acquisition of inflectional
morphemes by presenting pictures of creatures and identifying them with English-sounding
names. The most famous of these creatures is the wug. Berko would show a picture of
the creature along with the sentence “This is a wug.” A second picture was presented and
1The nasalization rule is also applied to get this form but I have not spelled it out in the section.
3
children were prompted with “Now, there’s another one. There are two of them. Now, there
are two . . . ?” where the expected response would be “wugs” and pronounced [w2gz]. If the
children were able to produce the proper pronunciation of the base noun with the affix, it
was assumed that the child had acquired the corresponding phonological rule.
In the case of [w2gz], if we assume that the underlying form of the morpheme -s is /z/,
then the phonological rule governing this for the case of /s/ is:
Rule 2. Assimilation
[+ voice] ! [- voice] /
2664
+ cons
- voice
3775
/z/ becomes /s/ after voiceless consonants.
and for the cases of -es, we will consider that /z/ is the underlying form but the following
happens to allow for the correct pronunciation:
Rule 3. Schwa insertion
; !
26666666666666666664
- front
- back
- round
- high
- low
- tense
37777777777777777775
/
266666666664
+ cons
+ cont
- son
- approx
377777777775
26666666666666666664
+ cons
+ cont
+ delayed release
- voice
- son
- approx
37777777777777777775
/@/ is inserted between a fricative or affricate and /s/.
We assume /z/ is the underlying form of -s because it occurs in more environments than
/s/ and /@s/. With these rules, we can generate the following phonological output:
4
cat dog horses
/kæt/ /dAg/ /hOôs/ lexical entries
Morphology
kæt-z dAg-z hOôs-z Plural
Phonology
/kætz/ /dAgz/ /hOôsz/ underlying forms
s – - Rule 2. Assimilation
- – @ Rule 3. Schwa insertion
[kæts] [dAgz] [hOôs@z] surface forms
Of course, these rules only apply to the -s suffix. Other morphological pluralization rules
exist (ex. mouse ! mice), but since Festival equates orthography with sound, we can assume
that there is very little morphology going on with irregular pluralization. Section 4 outlines
the results of Festival’s implementation of the phonological rules of pluralization.
2.3 Playing it by Ear
I believe that it will be a downfall of this experiment to rely on my intuitions of what I hear
and to use these subjective opinions as results. Nevertheless, this method is a necessary
consequence for my decision of not doing a comparison study of computer-generated English
as compared to a native English speaker. I would like to establish the study of whose
methodology I am influenced by.
Labov, in 1966, published a book on The Social Stratification of English in New York
City. This book was published as a result of a study he performed at three department
stores in New York City. The goal of the study was to analyze the difference in production
of a postvocalic [ô] and the absence of the postvocalic [ô] in terms of social rank. That is,
Labov visited three department stores that were considered to have different social ranking.
Saks was considered the upper class store, Macy’s was considered the middle class store, and
5
Klein was considered the lower class store. It was predicted that the employees of this store
would speak in a register that corresponds to the social rank of those who shop there, so
that an employee from Saks would speak in a upper-class register and so on. Labov designed
a small test for testing the presence the postvocalic [ô] by posing a question that requires
the response “fourth floor” which contains two instances of the target phoneme. He had
the employees repeat “fourth floor” a second time with careful speech. The results showed
that the employees at the upper class store, Saks, used the postvocalic [ô] most frequently
in regular speech and emphasized it the most when it was repeated. It was found with the
middle class store, Macy’s, that they would emphasize the postvocalic [ô] at the end of the
word (ie. “floor”) but not necessarily inside the world (ie. “fourth”). At the lower class
store, Klein, employees most often did not pronounce the postvocalic [ô] in regular speech
but often produced it in careful speech.
In its simplicity, Labov’s experiment is still respected even though he did not use technical
equipment other than his own ears for his judgements. I will choose to follow his methodology
and not consider it a downfall that I am playing it by ear, so to say. However, we will see in
the next section that I will use technology to strengthen my intuitions.
3 Methodology
The methodology section has been broken down in to sections 3.1 Materials and 3.2
Procedure.
3.1 Materials
The Festival Speech Synthesis System was used as the primary source of data. I used the
SLT American female English voice from the online version of Festival, available at http://
www.cstr.ed.ac.uk/projects/festival/onlinedemo.html. Research on the phonology
of the English language was used as a secondary source of data to compare with the data
6
from Festival (Hayes, 2009; Odden, 2005; O’Grady & Archibald, 2004; Berko, 1958; Labov,
1966). My own intuitions about English phonology were used as a third source of data, but
because of the comparison between American English and my own Canadian English dialect,
I did not heavily rely on these intuitions.
Raw .wav data was collected directly from Festival. It was saved and played back directly
through the sound card on a Gentoo Linux system using the following command:
aplay filename.wav
This method of playback allowed for the avoidance of any specialized filters from media
players. The output came from speakers. I was the only interpreter of the output. However,
Praat was also used to look at the waveforms and spectrograms of the .wav files (Boersma
& Weenink, 2009).
3.2 Procedure
Target sentences were created to elicit certain responses from Festival (see Appendix A
for the input). Festival was accessed online at http://www.cstr.ed.ac.uk/projects/
festival/onlinedemo.html and the target sentences were entered with the SLT American
female English voice selected. The resulting .wav files were stored on a computer.
The files were played back using the aplay command as discussed in section 3.1. They
were played multiple times each to guarantee a concise interpretation of the data. The
interpretations were recorded.
Praat was used, when applicable, to support the interpretations of the data.
4 Results
Festival failed the wug test. After collecting data from four target sentences (see Appendix
A) testing for /s/, /z/, and /@z/, Festival generated the following:
7
cat dog horses
/kæt/ /dAg/ /hOôs/ lexical entries
Morphology
kæt-s dAg-s hOôs-s Plural
Phonology
/kæts/ /dAgs/ /hOôss/ underlying forms
- – - Assimilation
- – @ Schwa insertion
[kæts] *[dAgs] *[hOôs@s] surface forms
5 Discussion
Out of the three target words for the wug test, [kæts], [dAgz], and [hOôs@z], only [kæts] was
produced correctly.
I believe that the correct production of [kæts] is actually the product of a mistake. In
section 2.2, I argued that /z/ was the underlying form of the morpheme -s because it was
the candidate for the elsewhere condition since its environments were not as easily predicted
as /s/ and /@z/. However, I argue that Festival chooses /s/ as the underlying form of -s.
This is not a radical suggestion since Festival relies on orthographic input and the written
letter “s” corresponds very often to the phoneme /s/ (but not in all cases, as outlined in
section 2.2).
If we assume that the assimilation rule is ignored, *[dAgs] can be produced. The same
output is produced for “wugs” as well. Festival produces *[w2gs]. This is not terribly
surprising because “dogs” and “wugs” share the environment of
g #
before the morphology is applied. What is surprising, however, is that the spectrograms of
the /gs/ portion of “dogs” and “wugs” are not identical (see Figures 1 and 2).
8
Time (s)
1.156 1.527
-0.268
0.2335
0
Now_there_are_two_dogs
Figure 1: Waveform of the /gs/ portion of “dogs.”
Time (s)
1.1 1.479
-0.2733
0.31
0
Now_there_are_two_wugs
Figure 2: Waveform of the /gs/ portion of “wugs.”
I was surprised by this data because I did not think a speech synthesis system would have
much room for variation of pronunciation, even within the same environments. I conducted
a test for variation by recording the sentence “Now there are two dogs” a second time and
compared the results in Praat. They were identical. This left the problem that there cannot
9
be variation within the synthesizer or else the two waveforms of “Now there are two dogs”
would be slightly different.
There is a potential answer to this issue. It could be that the /dA/ and /w2/ portions of
the words have some effect on the pronunciation of the rest of the word. This is somewhat
unintuitive. However, it may be a design approach from the developers of Festival to have
an overall assimilation algorithm that takes into account all of the sounds of an utterance
and apply some sort of blending to make the sounds sound similar. It is difficult to isolate
the exact reason why the /gs/ portions differ, especially since there seems to be no variation
within duplicated phrases.
It is interesting to note that Rule 2 Assimilation was ignored but Rule 3 Schwa insertion
was not. This can be proven by looking at waveforms of “horses” and “horse” (see Figures
3 and 4).
Time (s)
0.9103 1.61
-0.5416
0.934
0
Now_there_are_two_horses
Figure 3: Waveform of “horses.”
The /s/ sounds occurs where the waveband is most narrow. We can see in Figure 3 that
there is something between the two /s/. That would be the /@/. We can prove this even
further by looking at the spectrogram in Figure 5.
The /@/ is visible in Figure 5 by the dark formant bands. Formants show peak energy.
10
Time (s)
0.08155 0.6432
-0.5735
0.9899
0
horse
Figure 4: Waveform of “horse.”
Time (s)
1.11 1.66
0
5000
Frequency (Hz)
Figure 5: Spectrogram of /s@s/
Vowels have the highest sonority of any sounds, and thus, they have the most vocalic energy
and are easily spotted with formants. The /@/ is absent from Figure 4 so it cannot be in
the underlying form of “horse.”
So why is it that we have /@/ in the surface form of “horses” but we do not get the
11
assimilation rule to turn the second /s/ to /z/? It could be that schwa insertion may occur
because of some other rule of English, such as to block gemination. I tried to test this by
giving Festival the input “ss” but what resulted was [EsEs] as if Festival was “spelling out”
the letters rather than attempting to say them as a word. Because of this, it is difficult to
isolate why the /@/ appears.
6 Conclusion
In conclusion, Festival failed the wug test. Berko (1958) had success with children of just
5 years of age in her study and this sophisticated piece of software was unable to match
human-like speech with this test. This cannot discredit Festival completely as an inferior
product.
There are technical limitations to making sweeping generalizations about Festival through
this study. This was a study of just one of Festival’s voices. It could be true that this voice
has not been programmed to follow rules like English pluralization but other voices have.
This becomes a limitation of the voice and not of Festival itself.
I have made suggestions as to why Festival may have failed to produce the correct outputs.
It may be the case that it assumes /s/ to be the underlying phonetic form of -s in which
the assimilation rule is ignored. Also, schwa insertion may occur as a result of blocking
gemination or another such rule. This study cannot account for differences in the same
immediate phonetic environments. I have suggested that there may be a sort of smoothing
algorithm that is applied to the utterance as a whole. Further attempts to isolate these
particular issues are needed.
12
References
Berko, J. (1958). The child’s learning of English morphology. Word, 14, 150–177.
Boersma, P. & Weenink, D. (2009). Praat: Doing phonetics by computer. http://www.fon.
hum.uva.nl/praat/.
Chomsky, N. & Halle, M. (1968). The Sound Pattern of English. New York: Harper & Row.
Hayes, B. (2009). Introductory Phonology. Malden, MA: Wiley-Blackwell.
Labov, W. (1966). The Social Stratification of English in New York City. Washington, DC:
The Center for Applied Linguistics.
Odden, D. (2005). Introducing Phonology. Cambridge: Cambridge University Press.
O’Grady, W. & Archibald, J. (2004). Contemporary Linguistic Analysis (5th ed.). Toronto:
Pearson-Longman.
University of Edinburgh (2009). The festival speech synthesis system. http://www.cstr.
ed.ac.uk/projects/festival/.
13
A Appendix
The following are the items that were typed in to the Festival Speech Synthesis System at
http://www.cstr.ed.ac.uk/projects/festival/onlinedemo.html using the SLT American
female voice.
1. Now there are two cats.
2. Now there are two dogs. (x2)
3. Now there are two horses.
4. Now there are two wugs.
5. horse
14

source: http://crystal.dcbruce.com/wp-content/uploads/2010/08/3002-final-paper.pdf